Cure Model Regression
cureit.RdCure Model Regression
Usage
# S3 method for formula
cureit(
surv_formula,
cure_formula,
data,
conf.level = 0.95,
nboot = 100,
eps = 1e-07,
...
)
cureit(object, ...)
# S3 method for default
cureit(object, ...)Arguments
- surv_formula
formula with
Surv()on LHS and covariates on RHS.- cure_formula
formula with covariates for cure fraction on RHS
- data
data frame
- conf.level
confidence level. Default is 0.95.
- nboot
number of bootstrap samples used for inference.
- eps
convergence criterion for the EM algorithm.
- ...
passed to methods
- object
input object
See also
Other cureit() functions:
Brier_inference_bootstrap(),
broom_methods_cureit,
nomogram(),
predict.cureit()
Examples
cureit(surv_formula = Surv(ttdeath, death) ~ age + grade,
cure_formula = ~ age + grade, data = trial)
#> 0 were not able to fit
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002616112 0.569504769 0.345883977
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.575003030 0.009813492 0.108542405
#> grade_iii, Cure model
#> 0.823899189
#>
#> $surv_formula
#> Surv(ttdeath, death) ~ age + grade
#> <environment: 0x55d6f0c30f68>
#>
#> $cure_formula
#> ~age + grade
#> <environment: 0x55d6f0c30f68>
#>
#> $data
#> # A tibble: 200 × 8
#> trt age marker stage grade response death ttdeath
#> <chr> <dbl> <dbl> <fct> <fct> <int> <dbl> <dbl>
#> 1 Drug A 23 0.16 T1 II 0 0 24
#> 2 Drug B 9 1.11 T2 I 1 0 24
#> 3 Drug A 31 0.277 T1 II 0 0 24
#> 4 Drug A NA 2.07 T3 III 1 1 17.6
#> 5 Drug A 51 2.77 T4 III 1 1 16.4
#> 6 Drug B 39 0.613 T4 I 0 1 15.6
#> 7 Drug A 37 0.354 T1 II 0 0 24
#> 8 Drug A 32 1.74 T1 I 0 1 18.4
#> 9 Drug A 31 0.144 T1 II 0 0 24
#> 10 Drug B 34 0.205 T3 I 0 1 10.5
#> # ℹ 190 more rows
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> $surv_xlevels$grade
#> [1] "I" "II" "III"
#>
#>
#> $cure_xlevels
#> $cure_xlevels$grade
#> [1] "I" "II" "III"
#>
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 7
#> term estimate std.error statistic conf.low conf.high p.value
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure mod… -0.575 0.508 -1.13 -1.57 0.421 0.258
#> 2 age, Cure model 0.00981 0.0102 0.964 -0.0101 0.0298 0.335
#> 3 grade_ii, Cure model 0.109 0.350 0.310 -0.578 0.795 0.757
#> 4 grade_iii, Cure model 0.824 0.419 1.97 0.00305 1.64 0.0492
#>
#> $tidy$df_surv
#> # A tibble: 3 × 7
#> term estimate std.error statistic conf.low conf.high p.value
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00262 0.00849 -0.308 -0.0192 0.0140 0.758
#> 2 grade_ii, Survival mo… 0.570 0.271 2.10 0.0392 1.10 0.0353
#> 3 grade_iii, Survival m… 0.346 0.234 1.48 -0.114 0.805 0.140
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.575003 0.009813 0.108542 0.823899
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 253.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.575003030 0.009813492 0.108542405 0.823899189
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002616112 0.569504769 0.345883977
#>
#> $b_var
#> [1] 0.2582626740 0.0001037265 0.1228263462 0.1753938323
#>
#> $b_sd
#> [1] 0.50819551 0.01018462 0.35046590 0.41880047
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.1314603 0.9635599 0.3097089 1.9672834
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.25786141 0.33526660 0.75678234 0.04915055
#>
#> $beta_var
#> [1] 7.200999e-05 7.320815e-02 5.496806e-02
#>
#> $beta_sd
#> [1] 0.00848587 0.27057005 0.23445269
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.3082904 2.1048330 1.4752826
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.75786140 0.03530585 0.14013657
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.000000000 0.000000000 0.000000000 0.604678067 0.658063410 0.000000000
#> [7] 0.417229340 0.000000000 0.879376354 0.000000000 0.000000000 0.744886187
#> [13] 0.787600867 0.142672058 0.944518547 0.000000000 0.693100768 0.000000000
#> [19] 0.000000000 0.000000000 0.000000000 0.540871173 0.006912639 0.976381134
#> [25] 0.640373656 0.000000000 0.000000000 0.684419417 0.522291631 0.000000000
#> [31] 0.278243702 0.000000000 0.000000000 0.000000000 0.246976530 0.821307758
#> [37] 0.000000000 0.666890646 0.466018936 0.456394953 0.829660071 0.854634203
#> [43] 0.000000000 0.531599829 0.000000000 0.000000000 0.000000000 0.846335953
#> [49] 0.446649365 0.887603756 0.000000000 0.000000000 0.368370905 0.837991986
#> [55] 0.736284601 0.368370905 0.762052697 0.904005497 0.000000000 0.130947018
#> [61] 0.000000000 0.000000000 0.178167087 0.000000000 0.298558895 0.093531067
#> [67] 0.960518552 0.000000000 0.000000000 0.000000000 0.000000000 0.387858887
#> [73] 0.968455884 0.020860827 0.613665875 0.000000000 0.753465281 0.000000000
#> [79] 0.000000000 0.000000000 0.586773524 0.036370054 0.000000000 0.427038837
#> [85] 0.267747949 0.984266892 0.106209363 0.895813391 0.000000000 0.000000000
#> [91] 0.727657186 0.397671772 0.000000000 0.246976530 0.631469660 0.920311545
#> [97] 0.000000000 0.000000000 0.000000000 0.348502061 0.550166021 0.862915985
#> [103] 0.436874482 0.000000000 0.494318881 0.513013956 0.000000000 0.118522726
#> [109] 0.000000000 0.503694197 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.779118376 0.649247645 0.000000000 0.992139734 0.308649170
#> [121] 0.080274841 0.568542449 0.000000000 0.000000000 0.718999352 0.475516896
#> [127] 0.000000000 0.201867710 0.000000000 0.000000000 0.224987874 0.796088245
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.912176411 0.000000000
#> [139] 0.000000000 0.000000000 0.952539418 0.318644852 0.000000000 0.000000000
#> [145] 0.236117909 0.804529313 0.770582430 0.000000000 0.701722215 0.328677697
#> [151] 0.871155498 0.000000000 0.000000000 0.000000000 0.000000000 0.065734870
#> [157] 0.000000000 0.338572747 0.675684959 0.050684149 0.154512416 0.358472658
#> [163] 0.559374570 0.000000000 0.000000000 0.000000000 0.189977968 0.000000000
#> [169] 0.812910823 0.000000000 0.407438340 0.710355937 0.577676416 0.000000000
#> [175] 0.936485829 0.484909262 0.000000000 0.000000000 0.928419678 0.622583868
#> [181] 0.288505592 0.000000000 0.586773524 0.000000000 0.166456957 0.000000000
#> [187] 0.213576414 0.000000000 0.000000000
#>
#> $Time
#> 1 2 3 5 6 7 8 9 10 11 12 13 14
#> 24.00 24.00 24.00 16.43 15.64 24.00 18.43 24.00 10.53 24.00 24.00 14.34 12.89
#> 15 16 17 18 19 20 21 22 23 24 25 26 27
#> 22.68 8.71 24.00 15.21 24.00 24.00 24.00 24.00 16.92 23.89 6.32 15.77 24.00
#> 28 29 30 31 32 33 34 35 36 37 38 39 40
#> 24.00 15.45 17.43 24.00 20.90 24.00 24.00 24.00 21.19 12.52 24.00 15.59 18.00
#> 41 42 43 44 45 46 47 48 49 51 52 53 54
#> 18.02 12.43 12.10 24.00 17.42 24.00 24.00 24.00 12.19 18.23 10.42 24.00 24.00
#> 55 56 57 58 60 61 62 63 64 65 66 67 68
#> 19.34 12.21 14.46 19.34 13.15 10.12 24.00 22.77 24.00 24.00 22.13 24.00 20.62
#> 69 70 71 72 74 75 76 77 78 79 80 81 82
#> 23.23 7.38 24.00 24.00 24.00 24.00 19.22 7.27 23.88 16.23 24.00 14.06 24.00
#> 83 84 85 86 87 88 90 91 92 93 94 95 96
#> 24.00 24.00 16.44 23.81 24.00 18.37 20.94 5.33 22.92 10.33 24.00 24.00 14.54
#> 97 98 99 100 101 102 103 104 105 106 107 108 109
#> 19.14 24.00 21.19 16.07 9.97 24.00 24.00 24.00 19.75 16.67 11.18 18.29 24.00
#> 110 111 112 113 116 117 118 119 120 121 122 123 125
#> 17.56 17.45 24.00 22.86 24.00 17.46 24.00 24.00 24.00 24.00 24.00 13.00 15.65
#> 126 127 128 129 130 131 132 133 134 135 136 137 138
#> 24.00 3.53 20.35 23.41 16.47 24.00 24.00 14.65 17.81 24.00 21.83 24.00 24.00
#> 139 140 141 142 143 144 145 146 147 148 149 150 151
#> 21.49 12.68 24.00 24.00 24.00 24.00 10.07 24.00 24.00 24.00 8.37 20.33 24.00
#> 152 153 154 155 156 157 158 159 160 161 162 163 164
#> 24.00 21.33 12.63 13.08 24.00 15.10 20.14 10.55 24.00 24.00 24.00 24.00 23.60
#> 165 166 167 168 169 170 171 172 173 174 175 176 177
#> 24.00 19.98 15.55 23.72 22.41 19.54 16.57 24.00 24.00 24.00 21.91 24.00 12.53
#> 178 179 180 181 182 183 184 185 186 187 188 190 191
#> 24.00 18.63 14.82 16.46 24.00 9.24 17.77 24.00 24.00 9.92 16.16 20.81 24.00
#> 192 193 194 196 197 198 200
#> 16.44 24.00 22.40 24.00 21.60 24.00 24.00
#>
#> $bootstrap_fit
#> $bootstrap_fit[[1]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01496395 -0.01015668 -0.16043469
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.66986063 0.00608809 0.39795257
#> grade_iii, Cure model
#> 1.22105307
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 57 14.46 1 45 0 1
#> 133 14.65 1 57 0 0
#> 136 21.83 1 43 0 1
#> 91 5.33 1 61 0 1
#> 192 16.44 1 31 1 0
#> 101 9.97 1 10 0 1
#> 107 11.18 1 54 1 0
#> 4 17.64 1 NA 0 1
#> 29 15.45 1 68 1 0
#> 37 12.52 1 57 1 0
#> 181 16.46 1 45 0 1
#> 187 9.92 1 39 1 0
#> 153 21.33 1 55 1 0
#> 99 21.19 1 38 0 1
#> 117 17.46 1 26 0 1
#> 123 13.00 1 44 1 0
#> 155 13.08 1 26 0 0
#> 13 14.34 1 54 0 1
#> 145 10.07 1 65 1 0
#> 43 12.10 1 61 0 1
#> 69 23.23 1 25 0 1
#> 13.1 14.34 1 54 0 1
#> 157 15.10 1 47 0 0
#> 26 15.77 1 49 0 1
#> 49 12.19 1 48 1 0
#> 63 22.77 1 31 1 0
#> 153.1 21.33 1 55 1 0
#> 10 10.53 1 34 0 0
#> 88 18.37 1 47 0 0
#> 169 22.41 1 46 0 0
#> 179 18.63 1 42 0 0
#> 55 19.34 1 69 0 1
#> 56 12.21 1 60 0 0
#> 145.1 10.07 1 65 1 0
#> 195 11.76 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 57.1 14.46 1 45 0 1
#> 107.1 11.18 1 54 1 0
#> 63.1 22.77 1 31 1 0
#> 111 17.45 1 47 0 1
#> 189 10.51 1 NA 1 0
#> 69.1 23.23 1 25 0 1
#> 30 17.43 1 78 0 0
#> 81 14.06 1 34 0 0
#> 68.1 20.62 1 44 0 0
#> 111.1 17.45 1 47 0 1
#> 10.1 10.53 1 34 0 0
#> 166 19.98 1 48 0 0
#> 106 16.67 1 49 1 0
#> 195.1 11.76 1 NA 1 0
#> 192.1 16.44 1 31 1 0
#> 171 16.57 1 41 0 1
#> 76 19.22 1 54 0 1
#> 180 14.82 1 37 0 0
#> 23 16.92 1 61 0 0
#> 153.2 21.33 1 55 1 0
#> 139 21.49 1 63 1 0
#> 140 12.68 1 59 1 0
#> 145.2 10.07 1 65 1 0
#> 14 12.89 1 21 0 0
#> 199 19.81 1 NA 0 1
#> 187.1 9.92 1 39 1 0
#> 32 20.90 1 37 1 0
#> 93 10.33 1 52 0 1
#> 128 20.35 1 35 0 1
#> 79 16.23 1 54 1 0
#> 8 18.43 1 32 0 0
#> 89 11.44 1 NA 0 0
#> 114 13.68 1 NA 0 0
#> 76.1 19.22 1 54 0 1
#> 4.1 17.64 1 NA 0 1
#> 117.1 17.46 1 26 0 1
#> 15 22.68 1 48 0 0
#> 199.1 19.81 1 NA 0 1
#> 158 20.14 1 74 1 0
#> 101.1 9.97 1 10 0 1
#> 4.2 17.64 1 NA 0 1
#> 188 16.16 1 46 0 1
#> 181.1 16.46 1 45 0 1
#> 14.1 12.89 1 21 0 0
#> 153.3 21.33 1 55 1 0
#> 49.1 12.19 1 48 1 0
#> 108 18.29 1 39 0 1
#> 43.1 12.10 1 61 0 1
#> 97 19.14 1 65 0 1
#> 49.2 12.19 1 48 1 0
#> 158.1 20.14 1 74 1 0
#> 15.1 22.68 1 48 0 0
#> 85 16.44 1 36 0 0
#> 125 15.65 1 67 1 0
#> 36 21.19 1 48 0 1
#> 61 10.12 1 36 0 1
#> 57.2 14.46 1 45 0 1
#> 139.1 21.49 1 63 1 0
#> 69.2 23.23 1 25 0 1
#> 199.2 19.81 1 NA 0 1
#> 92 22.92 1 47 0 1
#> 50 10.02 1 NA 1 0
#> 69.3 23.23 1 25 0 1
#> 136.1 21.83 1 43 0 1
#> 149 8.37 1 33 1 0
#> 133.1 14.65 1 57 0 0
#> 4.3 17.64 1 NA 0 1
#> 183 9.24 1 67 1 0
#> 16 8.71 1 71 0 1
#> 18 15.21 1 49 1 0
#> 90 20.94 1 50 0 1
#> 23.1 16.92 1 61 0 0
#> 30.1 17.43 1 78 0 0
#> 170 19.54 1 43 0 1
#> 127 3.53 1 62 0 1
#> 39 15.59 1 37 0 1
#> 33 24.00 0 53 0 0
#> 156 24.00 0 50 1 0
#> 135 24.00 0 58 1 0
#> 182 24.00 0 35 0 0
#> 176 24.00 0 43 0 1
#> 65 24.00 0 57 1 0
#> 104 24.00 0 50 1 0
#> 103 24.00 0 56 1 0
#> 182.1 24.00 0 35 0 0
#> 47 24.00 0 38 0 1
#> 7 24.00 0 37 1 0
#> 33.1 24.00 0 53 0 0
#> 135.1 24.00 0 58 1 0
#> 141 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 172 24.00 0 41 0 0
#> 104.1 24.00 0 50 1 0
#> 178 24.00 0 52 1 0
#> 176.1 24.00 0 43 0 1
#> 185 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 98 24.00 0 34 1 0
#> 35 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 196 24.00 0 19 0 0
#> 98.1 24.00 0 34 1 0
#> 109 24.00 0 48 0 0
#> 53 24.00 0 32 0 1
#> 19 24.00 0 57 0 1
#> 3 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 198 24.00 0 66 0 1
#> 7.1 24.00 0 37 1 0
#> 185.1 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 126 24.00 0 48 0 0
#> 9 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 119 24.00 0 17 0 0
#> 21 24.00 0 47 0 0
#> 162.1 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 98.2 24.00 0 34 1 0
#> 200 24.00 0 64 0 0
#> 163 24.00 0 66 0 0
#> 112.1 24.00 0 61 0 0
#> 19.1 24.00 0 57 0 1
#> 182.2 24.00 0 35 0 0
#> 144 24.00 0 28 0 1
#> 143 24.00 0 51 0 0
#> 193 24.00 0 45 0 1
#> 83 24.00 0 6 0 0
#> 144.1 24.00 0 28 0 1
#> 162.2 24.00 0 51 0 0
#> 65.1 24.00 0 57 1 0
#> 163.1 24.00 0 66 0 0
#> 186 24.00 0 45 1 0
#> 28 24.00 0 67 1 0
#> 119.1 24.00 0 17 0 0
#> 27.1 24.00 0 63 1 0
#> 71.1 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 137 24.00 0 45 1 0
#> 112.2 24.00 0 61 0 0
#> 3.1 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 178.1 24.00 0 52 1 0
#> 87.1 24.00 0 27 0 0
#> 72 24.00 0 40 0 1
#> 11 24.00 0 42 0 1
#> 156.1 24.00 0 50 1 0
#> 146 24.00 0 63 1 0
#> 2 24.00 0 9 0 0
#> 62 24.00 0 71 0 0
#> 185.2 24.00 0 44 1 0
#> 21.1 24.00 0 47 0 0
#> 112.3 24.00 0 61 0 0
#> 95.1 24.00 0 68 0 1
#> 115 24.00 0 NA 1 0
#> 144.2 24.00 0 28 0 1
#> 1 24.00 0 23 1 0
#> 132 24.00 0 55 0 0
#> 198.1 24.00 0 66 0 1
#> 126.1 24.00 0 48 0 0
#> 138 24.00 0 44 1 0
#> 12 24.00 0 63 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.670 NA NA NA
#> 2 age, Cure model 0.00609 NA NA NA
#> 3 grade_ii, Cure model 0.398 NA NA NA
#> 4 grade_iii, Cure model 1.22 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0150 NA NA NA
#> 2 grade_ii, Survival model -0.0102 NA NA NA
#> 3 grade_iii, Survival model -0.160 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.669861 0.006088 0.397953 1.221053
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 257.1
#> Residual Deviance: 246 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.66986063 0.00608809 0.39795257 1.22105307
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01496395 -0.01015668 -0.16043469
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.7938920 0.7810688 0.3059958 0.9896044 0.6982205 0.9523481 0.9026944
#> [8] 0.7544260 0.8619841 0.6836497 0.9631175 0.3688870 0.4160355 0.6048292
#> [15] 0.8375895 0.8313984 0.8127441 0.9362418 0.8912640 0.0779458 0.8127441
#> [22] 0.7678585 0.7336920 0.8739250 0.2030544 0.3688870 0.9139507 0.5877266
#> [29] 0.2873596 0.5702183 0.5338738 0.8679844 0.9362418 0.4624981 0.7938920
#> [36] 0.9026944 0.2030544 0.6216266 0.0779458 0.6381031 0.8251853 0.4624981
#> [43] 0.6216266 0.9139507 0.5145224 0.6687398 0.6982205 0.6762183 0.5432586
#> [50] 0.7744845 0.6536890 0.3688870 0.3396705 0.8559281 0.9362418 0.8437390
#> [57] 0.9631175 0.4510871 0.9251158 0.4840600 0.7195501 0.5790131 0.5432586
#> [64] 0.6048292 0.2489112 0.4948572 0.9523481 0.7266449 0.6836497 0.8437390
#> [71] 0.3688870 0.8739250 0.5963102 0.8912640 0.5613033 0.8739250 0.4948572
#> [78] 0.2489112 0.6982205 0.7406870 0.4160355 0.9306864 0.7938920 0.3396705
#> [85] 0.0779458 0.1747984 0.0779458 0.3059958 0.9843599 0.7810688 0.9737943
#> [92] 0.9790980 0.7611737 0.4394637 0.6536890 0.6381031 0.5242535 0.9948179
#> [99] 0.7475717 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 57 133 136 91 192 101 107 29 37 181 187 153 99
#> 14.46 14.65 21.83 5.33 16.44 9.97 11.18 15.45 12.52 16.46 9.92 21.33 21.19
#> 117 123 155 13 145 43 69 13.1 157 26 49 63 153.1
#> 17.46 13.00 13.08 14.34 10.07 12.10 23.23 14.34 15.10 15.77 12.19 22.77 21.33
#> 10 88 169 179 55 56 145.1 68 57.1 107.1 63.1 111 69.1
#> 10.53 18.37 22.41 18.63 19.34 12.21 10.07 20.62 14.46 11.18 22.77 17.45 23.23
#> 30 81 68.1 111.1 10.1 166 106 192.1 171 76 180 23 153.2
#> 17.43 14.06 20.62 17.45 10.53 19.98 16.67 16.44 16.57 19.22 14.82 16.92 21.33
#> 139 140 145.2 14 187.1 32 93 128 79 8 76.1 117.1 15
#> 21.49 12.68 10.07 12.89 9.92 20.90 10.33 20.35 16.23 18.43 19.22 17.46 22.68
#> 158 101.1 188 181.1 14.1 153.3 49.1 108 43.1 97 49.2 158.1 15.1
#> 20.14 9.97 16.16 16.46 12.89 21.33 12.19 18.29 12.10 19.14 12.19 20.14 22.68
#> 85 125 36 61 57.2 139.1 69.2 92 69.3 136.1 149 133.1 183
#> 16.44 15.65 21.19 10.12 14.46 21.49 23.23 22.92 23.23 21.83 8.37 14.65 9.24
#> 16 18 90 23.1 30.1 170 127 39 33 156 135 182 176
#> 8.71 15.21 20.94 16.92 17.43 19.54 3.53 15.59 24.00 24.00 24.00 24.00 24.00
#> 65 104 103 182.1 47 7 33.1 135.1 141 112 172 104.1 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 185 162 27 98 35 121 196 98.1 109 53 19 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 198 7.1 185.1 34 126 9 71 116 119 21 162.1 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.2 200 163 112.1 19.1 182.2 144 143 193 83 144.1 162.2 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163.1 186 28 119.1 27.1 71.1 87 137 112.2 3.1 95 178.1 87.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 11 156.1 146 2 62 185.2 21.1 112.3 95.1 144.2 1 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198.1 126.1 138 12
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[2]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008082288 0.553868991 0.168075885
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.76011346 0.01285107 0.09838250
#> grade_iii, Cure model
#> 0.79177494
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 111 17.45 1 47 0 1
#> 85 16.44 1 36 0 0
#> 50 10.02 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 93 10.33 1 52 0 1
#> 153 21.33 1 55 1 0
#> 90 20.94 1 50 0 1
#> 180 14.82 1 37 0 0
#> 51 18.23 1 83 0 1
#> 169 22.41 1 46 0 0
#> 183 9.24 1 67 1 0
#> 10 10.53 1 34 0 0
#> 168 23.72 1 70 0 0
#> 13 14.34 1 54 0 1
#> 179 18.63 1 42 0 0
#> 164 23.60 1 76 0 1
#> 39 15.59 1 37 0 1
#> 159 10.55 1 50 0 1
#> 69 23.23 1 25 0 1
#> 61 10.12 1 36 0 1
#> 29 15.45 1 68 1 0
#> 32 20.90 1 37 1 0
#> 197 21.60 1 69 1 0
#> 96 14.54 1 33 0 1
#> 8 18.43 1 32 0 0
#> 97 19.14 1 65 0 1
#> 57 14.46 1 45 0 1
#> 183.1 9.24 1 67 1 0
#> 5 16.43 1 51 0 1
#> 61.1 10.12 1 36 0 1
#> 92 22.92 1 47 0 1
#> 114 13.68 1 NA 0 0
#> 81 14.06 1 34 0 0
#> 37 12.52 1 57 1 0
#> 129 23.41 1 53 1 0
#> 70 7.38 1 30 1 0
#> 63 22.77 1 31 1 0
#> 107 11.18 1 54 1 0
#> 114.1 13.68 1 NA 0 0
#> 45 17.42 1 54 0 1
#> 92.1 22.92 1 47 0 1
#> 177.1 12.53 1 75 0 0
#> 61.2 10.12 1 36 0 1
#> 199 19.81 1 NA 0 1
#> 127 3.53 1 62 0 1
#> 180.1 14.82 1 37 0 0
#> 61.3 10.12 1 36 0 1
#> 45.1 17.42 1 54 0 1
#> 157 15.10 1 47 0 0
#> 97.1 19.14 1 65 0 1
#> 69.1 23.23 1 25 0 1
#> 134 17.81 1 47 1 0
#> 76 19.22 1 54 0 1
#> 177.2 12.53 1 75 0 0
#> 145 10.07 1 65 1 0
#> 86 23.81 1 58 0 1
#> 32.1 20.90 1 37 1 0
#> 194 22.40 1 38 0 1
#> 187 9.92 1 39 1 0
#> 96.1 14.54 1 33 0 1
#> 145.1 10.07 1 65 1 0
#> 59 10.16 1 NA 1 0
#> 96.2 14.54 1 33 0 1
#> 4 17.64 1 NA 0 1
#> 140 12.68 1 59 1 0
#> 39.1 15.59 1 37 0 1
#> 76.1 19.22 1 54 0 1
#> 25 6.32 1 34 1 0
#> 51.1 18.23 1 83 0 1
#> 179.1 18.63 1 42 0 0
#> 10.1 10.53 1 34 0 0
#> 117 17.46 1 26 0 1
#> 15 22.68 1 48 0 0
#> 164.1 23.60 1 76 0 1
#> 164.2 23.60 1 76 0 1
#> 187.1 9.92 1 39 1 0
#> 166 19.98 1 48 0 0
#> 124 9.73 1 NA 1 0
#> 57.1 14.46 1 45 0 1
#> 63.1 22.77 1 31 1 0
#> 90.1 20.94 1 50 0 1
#> 14 12.89 1 21 0 0
#> 114.2 13.68 1 NA 0 0
#> 158 20.14 1 74 1 0
#> 181 16.46 1 45 0 1
#> 189 10.51 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 195 11.76 1 NA 1 0
#> 14.1 12.89 1 21 0 0
#> 5.1 16.43 1 51 0 1
#> 93.1 10.33 1 52 0 1
#> 189.1 10.51 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 169.1 22.41 1 46 0 0
#> 78 23.88 1 43 0 0
#> 39.2 15.59 1 37 0 1
#> 189.2 10.51 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 88 18.37 1 47 0 0
#> 32.2 20.90 1 37 1 0
#> 24 23.89 1 38 0 0
#> 86.1 23.81 1 58 0 1
#> 175 21.91 1 43 0 0
#> 60 13.15 1 38 1 0
#> 37.1 12.52 1 57 1 0
#> 154 12.63 1 20 1 0
#> 124.1 9.73 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 66 22.13 1 53 0 0
#> 14.2 12.89 1 21 0 0
#> 184 17.77 1 38 0 0
#> 188 16.16 1 46 0 1
#> 83 24.00 0 6 0 0
#> 47 24.00 0 38 0 1
#> 71 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 48.1 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 115 24.00 0 NA 1 0
#> 144 24.00 0 28 0 1
#> 21 24.00 0 47 0 0
#> 144.1 24.00 0 28 0 1
#> 118 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 83.1 24.00 0 6 0 0
#> 34 24.00 0 36 0 0
#> 144.2 24.00 0 28 0 1
#> 12 24.00 0 63 0 0
#> 116 24.00 0 58 0 1
#> 34.1 24.00 0 36 0 0
#> 147 24.00 0 76 1 0
#> 151 24.00 0 42 0 0
#> 2 24.00 0 9 0 0
#> 122 24.00 0 66 0 0
#> 200 24.00 0 64 0 0
#> 176 24.00 0 43 0 1
#> 35 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 160 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 98 24.00 0 34 1 0
#> 198.1 24.00 0 66 0 1
#> 115.1 24.00 0 NA 1 0
#> 144.3 24.00 0 28 0 1
#> 53 24.00 0 32 0 1
#> 152 24.00 0 36 0 1
#> 54 24.00 0 53 1 0
#> 200.1 24.00 0 64 0 0
#> 198.2 24.00 0 66 0 1
#> 186 24.00 0 45 1 0
#> 146 24.00 0 63 1 0
#> 11 24.00 0 42 0 1
#> 165 24.00 0 47 0 0
#> 28 24.00 0 67 1 0
#> 62 24.00 0 71 0 0
#> 198.3 24.00 0 66 0 1
#> 122.1 24.00 0 66 0 0
#> 11.1 24.00 0 42 0 1
#> 7 24.00 0 37 1 0
#> 9 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 178 24.00 0 52 1 0
#> 83.2 24.00 0 6 0 0
#> 174 24.00 0 49 1 0
#> 38 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 3 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 38.1 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 162.1 24.00 0 51 0 0
#> 9.1 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 112 24.00 0 61 0 0
#> 19.1 24.00 0 57 0 1
#> 98.1 24.00 0 34 1 0
#> 35.1 24.00 0 51 0 0
#> 146.1 24.00 0 63 1 0
#> 161.1 24.00 0 45 0 0
#> 156 24.00 0 50 1 0
#> 80.1 24.00 0 41 0 0
#> 75 24.00 0 21 1 0
#> 35.2 24.00 0 51 0 0
#> 162.2 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 152.1 24.00 0 36 0 1
#> 200.2 24.00 0 64 0 0
#> 151.1 24.00 0 42 0 0
#> 20 24.00 0 46 1 0
#> 121 24.00 0 57 1 0
#> 186.1 24.00 0 45 1 0
#> 9.2 24.00 0 31 1 0
#> 47.1 24.00 0 38 0 1
#> 178.1 24.00 0 52 1 0
#> 94 24.00 0 51 0 1
#> 161.2 24.00 0 45 0 0
#> 143 24.00 0 51 0 0
#> 19.2 24.00 0 57 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.760 NA NA NA
#> 2 age, Cure model 0.0129 NA NA NA
#> 3 grade_ii, Cure model 0.0984 NA NA NA
#> 4 grade_iii, Cure model 0.792 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00808 NA NA NA
#> 2 grade_ii, Survival model 0.554 NA NA NA
#> 3 grade_iii, Survival model 0.168 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.76011 0.01285 0.09838 0.79177
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.6
#> Residual Deviance: 247.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.76011346 0.01285107 0.09838250 0.79177494
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008082288 0.553868991 0.168075885
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.387802347 0.429617328 0.703242866 0.805297171 0.176294442 0.185718776
#> [7] 0.536915480 0.336450729 0.121411020 0.919880223 0.782469796 0.023128336
#> [13] 0.613677850 0.296818256 0.030801063 0.483145680 0.771052275 0.062477400
#> [19] 0.828269739 0.515092124 0.204480616 0.166811671 0.558815744 0.316358403
#> [25] 0.277641808 0.591521454 0.919880223 0.440269818 0.828269739 0.079100560
#> [31] 0.624906039 0.737034633 0.053624369 0.954284289 0.096430282 0.759670192
#> [37] 0.398218384 0.079100560 0.703242866 0.828269739 0.988535291 0.536915480
#> [43] 0.828269739 0.398218384 0.525968027 0.277641808 0.062477400 0.356813728
#> [49] 0.258855522 0.703242866 0.873866696 0.011666636 0.204480616 0.138899787
#> [55] 0.896952971 0.558815744 0.873866696 0.558815744 0.680754049 0.483145680
#> [61] 0.258855522 0.965717909 0.336450729 0.296818256 0.782469796 0.377439448
#> [67] 0.112732115 0.030801063 0.030801063 0.896952971 0.240138355 0.591521454
#> [73] 0.096430282 0.185718776 0.647404138 0.230941939 0.419031114 0.942800403
#> [79] 0.647404138 0.440269818 0.805297171 0.249449462 0.121411020 0.005831320
#> [85] 0.483145680 0.977108122 0.326355690 0.204480616 0.001497399 0.011666636
#> [91] 0.157331093 0.636182917 0.737034633 0.692042327 0.472343089 0.148015432
#> [97] 0.647404138 0.367088274 0.461537438 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 111 85 177 93 153 90 180 51 169 183 10 168 13
#> 17.45 16.44 12.53 10.33 21.33 20.94 14.82 18.23 22.41 9.24 10.53 23.72 14.34
#> 179 164 39 159 69 61 29 32 197 96 8 97 57
#> 18.63 23.60 15.59 10.55 23.23 10.12 15.45 20.90 21.60 14.54 18.43 19.14 14.46
#> 183.1 5 61.1 92 81 37 129 70 63 107 45 92.1 177.1
#> 9.24 16.43 10.12 22.92 14.06 12.52 23.41 7.38 22.77 11.18 17.42 22.92 12.53
#> 61.2 127 180.1 61.3 45.1 157 97.1 69.1 134 76 177.2 145 86
#> 10.12 3.53 14.82 10.12 17.42 15.10 19.14 23.23 17.81 19.22 12.53 10.07 23.81
#> 32.1 194 187 96.1 145.1 96.2 140 39.1 76.1 25 51.1 179.1 10.1
#> 20.90 22.40 9.92 14.54 10.07 14.54 12.68 15.59 19.22 6.32 18.23 18.63 10.53
#> 117 15 164.1 164.2 187.1 166 57.1 63.1 90.1 14 158 181 149
#> 17.46 22.68 23.60 23.60 9.92 19.98 14.46 22.77 20.94 12.89 20.14 16.46 8.37
#> 14.1 5.1 93.1 58 169.1 78 39.2 91 88 32.2 24 86.1 175
#> 12.89 16.43 10.33 19.34 22.41 23.88 15.59 5.33 18.37 20.90 23.89 23.81 21.91
#> 60 37.1 154 125 66 14.2 184 188 83 47 71 48 198
#> 13.15 12.52 12.63 15.65 22.13 12.89 17.77 16.16 24.00 24.00 24.00 24.00 24.00
#> 48.1 104 144 21 144.1 118 80 83.1 34 144.2 12 116 34.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 151 2 122 200 176 35 31 160 119 98 198.1 144.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 152 54 200.1 198.2 186 146 11 165 28 62 198.3 122.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.1 7 9 82 178 83.2 174 38 95 3 67 38.1 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 162.1 9.1 161 112 19.1 98.1 35.1 146.1 161.1 156 80.1 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.2 162.2 1 152.1 200.2 151.1 20 121 186.1 9.2 47.1 178.1 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.2 143 19.2
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[3]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0007180592 0.5715320486 0.3275310586
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.42888277 0.01029063 -0.09207609
#> grade_iii, Cure model
#> 0.57210916
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 78 23.88 1 43 0 0
#> 14 12.89 1 21 0 0
#> 100 16.07 1 60 0 0
#> 106 16.67 1 49 1 0
#> 125 15.65 1 67 1 0
#> 113 22.86 1 34 0 0
#> 114 13.68 1 NA 0 0
#> 30 17.43 1 78 0 0
#> 184 17.77 1 38 0 0
#> 24 23.89 1 38 0 0
#> 93 10.33 1 52 0 1
#> 130 16.47 1 53 0 1
#> 169 22.41 1 46 0 0
#> 39 15.59 1 37 0 1
#> 184.1 17.77 1 38 0 0
#> 155 13.08 1 26 0 0
#> 145 10.07 1 65 1 0
#> 129 23.41 1 53 1 0
#> 69 23.23 1 25 0 1
#> 60 13.15 1 38 1 0
#> 110 17.56 1 65 0 1
#> 52 10.42 1 52 0 1
#> 107 11.18 1 54 1 0
#> 187 9.92 1 39 1 0
#> 59 10.16 1 NA 1 0
#> 60.1 13.15 1 38 1 0
#> 139 21.49 1 63 1 0
#> 88 18.37 1 47 0 0
#> 150 20.33 1 48 0 0
#> 113.1 22.86 1 34 0 0
#> 81 14.06 1 34 0 0
#> 105 19.75 1 60 0 0
#> 89 11.44 1 NA 0 0
#> 90 20.94 1 50 0 1
#> 180 14.82 1 37 0 0
#> 90.1 20.94 1 50 0 1
#> 194 22.40 1 38 0 1
#> 199 19.81 1 NA 0 1
#> 32 20.90 1 37 1 0
#> 101 9.97 1 10 0 1
#> 155.1 13.08 1 26 0 0
#> 90.2 20.94 1 50 0 1
#> 188 16.16 1 46 0 1
#> 195 11.76 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 171 16.57 1 41 0 1
#> 15 22.68 1 48 0 0
#> 39.1 15.59 1 37 0 1
#> 150.1 20.33 1 48 0 0
#> 183 9.24 1 67 1 0
#> 184.2 17.77 1 38 0 0
#> 76 19.22 1 54 0 1
#> 43 12.10 1 61 0 1
#> 181 16.46 1 45 0 1
#> 183.1 9.24 1 67 1 0
#> 169.1 22.41 1 46 0 0
#> 68 20.62 1 44 0 0
#> 16 8.71 1 71 0 1
#> 86 23.81 1 58 0 1
#> 86.1 23.81 1 58 0 1
#> 88.1 18.37 1 47 0 0
#> 128 20.35 1 35 0 1
#> 117 17.46 1 26 0 1
#> 149 8.37 1 33 1 0
#> 32.1 20.90 1 37 1 0
#> 181.1 16.46 1 45 0 1
#> 42 12.43 1 49 0 1
#> 40 18.00 1 28 1 0
#> 36 21.19 1 48 0 1
#> 39.2 15.59 1 37 0 1
#> 171.1 16.57 1 41 0 1
#> 181.2 16.46 1 45 0 1
#> 188.1 16.16 1 46 0 1
#> 113.2 22.86 1 34 0 0
#> 45 17.42 1 54 0 1
#> 199.1 19.81 1 NA 0 1
#> 136 21.83 1 43 0 1
#> 13 14.34 1 54 0 1
#> 188.2 16.16 1 46 0 1
#> 86.2 23.81 1 58 0 1
#> 192 16.44 1 31 1 0
#> 78.1 23.88 1 43 0 0
#> 113.3 22.86 1 34 0 0
#> 129.1 23.41 1 53 1 0
#> 29 15.45 1 68 1 0
#> 23 16.92 1 61 0 0
#> 177 12.53 1 75 0 0
#> 55 19.34 1 69 0 1
#> 114.1 13.68 1 NA 0 0
#> 194.1 22.40 1 38 0 1
#> 175 21.91 1 43 0 0
#> 190 20.81 1 42 1 0
#> 184.3 17.77 1 38 0 0
#> 30.1 17.43 1 78 0 0
#> 76.1 19.22 1 54 0 1
#> 111 17.45 1 47 0 1
#> 50 10.02 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 52.1 10.42 1 52 0 1
#> 59.1 10.16 1 NA 1 0
#> 181.3 16.46 1 45 0 1
#> 23.1 16.92 1 61 0 0
#> 41 18.02 1 40 1 0
#> 107.1 11.18 1 54 1 0
#> 192.1 16.44 1 31 1 0
#> 23.2 16.92 1 61 0 0
#> 50.1 10.02 1 NA 1 0
#> 36.1 21.19 1 48 0 1
#> 139.1 21.49 1 63 1 0
#> 139.2 21.49 1 63 1 0
#> 70 7.38 1 30 1 0
#> 10 10.53 1 34 0 0
#> 53 24.00 0 32 0 1
#> 104 24.00 0 50 1 0
#> 2 24.00 0 9 0 0
#> 34 24.00 0 36 0 0
#> 174 24.00 0 49 1 0
#> 193 24.00 0 45 0 1
#> 119 24.00 0 17 0 0
#> 119.1 24.00 0 17 0 0
#> 162 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 1 24.00 0 23 1 0
#> 115 24.00 0 NA 1 0
#> 161 24.00 0 45 0 0
#> 74 24.00 0 43 0 1
#> 46 24.00 0 71 0 0
#> 193.1 24.00 0 45 0 1
#> 121 24.00 0 57 1 0
#> 102 24.00 0 49 0 0
#> 137 24.00 0 45 1 0
#> 193.2 24.00 0 45 0 1
#> 185 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 64 24.00 0 43 0 0
#> 198 24.00 0 66 0 1
#> 147 24.00 0 76 1 0
#> 46.1 24.00 0 71 0 0
#> 67 24.00 0 25 0 0
#> 126 24.00 0 48 0 0
#> 142 24.00 0 53 0 0
#> 65 24.00 0 57 1 0
#> 115.1 24.00 0 NA 1 0
#> 67.1 24.00 0 25 0 0
#> 200 24.00 0 64 0 0
#> 72 24.00 0 40 0 1
#> 143 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 126.1 24.00 0 48 0 0
#> 95 24.00 0 68 0 1
#> 144 24.00 0 28 0 1
#> 98 24.00 0 34 1 0
#> 132 24.00 0 55 0 0
#> 95.1 24.00 0 68 0 1
#> 185.1 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 84 24.00 0 39 0 1
#> 163 24.00 0 66 0 0
#> 73 24.00 0 NA 0 1
#> 112 24.00 0 61 0 0
#> 12 24.00 0 63 0 0
#> 178 24.00 0 52 1 0
#> 141 24.00 0 44 1 0
#> 94 24.00 0 51 0 1
#> 142.1 24.00 0 53 0 0
#> 20 24.00 0 46 1 0
#> 115.2 24.00 0 NA 1 0
#> 196 24.00 0 19 0 0
#> 75 24.00 0 21 1 0
#> 138 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 185.2 24.00 0 44 1 0
#> 2.1 24.00 0 9 0 0
#> 11 24.00 0 42 0 1
#> 144.1 24.00 0 28 0 1
#> 119.2 24.00 0 17 0 0
#> 12.1 24.00 0 63 0 0
#> 185.3 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 73.1 24.00 0 NA 0 1
#> 104.1 24.00 0 50 1 0
#> 83 24.00 0 6 0 0
#> 9 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 28 24.00 0 67 1 0
#> 3 24.00 0 31 1 0
#> 138.1 24.00 0 44 1 0
#> 48.1 24.00 0 31 1 0
#> 95.2 24.00 0 68 0 1
#> 46.2 24.00 0 71 0 0
#> 84.1 24.00 0 39 0 1
#> 72.1 24.00 0 40 0 1
#> 27.1 24.00 0 63 1 0
#> 34.1 24.00 0 36 0 0
#> 74.1 24.00 0 43 0 1
#> 126.2 24.00 0 48 0 0
#> 176 24.00 0 43 0 1
#> 185.4 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.429 NA NA NA
#> 2 age, Cure model 0.0103 NA NA NA
#> 3 grade_ii, Cure model -0.0921 NA NA NA
#> 4 grade_iii, Cure model 0.572 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000718 NA NA NA
#> 2 grade_ii, Survival model 0.572 NA NA NA
#> 3 grade_iii, Survival model 0.328 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.42888 0.01029 -0.09208 0.57211
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 254.5
#> Residual Deviance: 249.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.42888277 0.01029063 -0.09207609 0.57210916
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0007180592 0.5715320486 0.3275310586
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.04729799 0.86918506 0.75389719 0.64754338 0.76189216 0.17543926
#> [7] 0.59566605 0.53409629 0.01787468 0.93586386 0.67304157 0.23617945
#> [13] 0.76981578 0.53409629 0.85417826 0.94315697 0.13528794 0.16197365
#> [19] 0.83916650 0.56912601 0.92128465 0.89923046 0.95762543 0.83916650
#> [25] 0.31009887 0.49762271 0.44141037 0.17543926 0.83151399 0.46028296
#> [31] 0.36310797 0.80848505 0.36310797 0.26138533 0.39311425 0.95040215
#> [37] 0.85417826 0.36310797 0.73015477 0.81617391 0.65614326 0.22317446
#> [43] 0.76981578 0.44141037 0.96480425 0.53409629 0.47924807 0.89175519
#> [49] 0.68149729 0.96480425 0.23617945 0.42221259 0.97892874 0.09034519
#> [55] 0.09034519 0.49762271 0.43185658 0.57802949 0.98599311 0.39311425
#> [61] 0.68149729 0.88425164 0.52509831 0.34204512 0.76981578 0.65614326
#> [67] 0.68149729 0.73015477 0.17543926 0.61308591 0.29795751 0.82385974
#> [73] 0.73015477 0.09034519 0.71401033 0.04729799 0.17543926 0.13528794
#> [79] 0.79304126 0.62180342 0.87672014 0.46980934 0.26138533 0.28559918
#> [85] 0.41256153 0.53409629 0.59566605 0.47924807 0.58687660 0.80079422
#> [91] 0.92128465 0.68149729 0.62180342 0.51597418 0.89923046 0.71401033
#> [97] 0.62180342 0.34204512 0.31009887 0.31009887 0.99301655 0.91391441
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 78 14 100 106 125 113 30 184 24 93 130 169 39
#> 23.88 12.89 16.07 16.67 15.65 22.86 17.43 17.77 23.89 10.33 16.47 22.41 15.59
#> 184.1 155 145 129 69 60 110 52 107 187 60.1 139 88
#> 17.77 13.08 10.07 23.41 23.23 13.15 17.56 10.42 11.18 9.92 13.15 21.49 18.37
#> 150 113.1 81 105 90 180 90.1 194 32 101 155.1 90.2 188
#> 20.33 22.86 14.06 19.75 20.94 14.82 20.94 22.40 20.90 9.97 13.08 20.94 16.16
#> 133 171 15 39.1 150.1 183 184.2 76 43 181 183.1 169.1 68
#> 14.65 16.57 22.68 15.59 20.33 9.24 17.77 19.22 12.10 16.46 9.24 22.41 20.62
#> 16 86 86.1 88.1 128 117 149 32.1 181.1 42 40 36 39.2
#> 8.71 23.81 23.81 18.37 20.35 17.46 8.37 20.90 16.46 12.43 18.00 21.19 15.59
#> 171.1 181.2 188.1 113.2 45 136 13 188.2 86.2 192 78.1 113.3 129.1
#> 16.57 16.46 16.16 22.86 17.42 21.83 14.34 16.16 23.81 16.44 23.88 22.86 23.41
#> 29 23 177 55 194.1 175 190 184.3 30.1 76.1 111 18 52.1
#> 15.45 16.92 12.53 19.34 22.40 21.91 20.81 17.77 17.43 19.22 17.45 15.21 10.42
#> 181.3 23.1 41 107.1 192.1 23.2 36.1 139.1 139.2 70 10 53 104
#> 16.46 16.92 18.02 11.18 16.44 16.92 21.19 21.49 21.49 7.38 10.53 24.00 24.00
#> 2 34 174 193 119 119.1 162 109 1 161 74 46 193.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 102 137 193.2 185 21 64 198 147 46.1 67 126 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 67.1 200 72 143 165 126.1 95 144 98 132 95.1 185.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 31 84 163 112 12 178 141 94 142.1 20 196 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 27 185.2 2.1 11 144.1 119.2 12.1 185.3 17 104.1 83 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 28 3 138.1 48.1 95.2 46.2 84.1 72.1 27.1 34.1 74.1 126.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 185.4 120
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[4]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005619827 0.407293565 0.447655993
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.66419280 0.01250875 0.19780965
#> grade_iii, Cure model
#> 0.55401038
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 105 19.75 1 60 0 0
#> 36 21.19 1 48 0 1
#> 8 18.43 1 32 0 0
#> 86 23.81 1 58 0 1
#> 26 15.77 1 49 0 1
#> 150 20.33 1 48 0 0
#> 58 19.34 1 39 0 0
#> 107 11.18 1 54 1 0
#> 13 14.34 1 54 0 1
#> 194 22.40 1 38 0 1
#> 139 21.49 1 63 1 0
#> 150.1 20.33 1 48 0 0
#> 45 17.42 1 54 0 1
#> 66 22.13 1 53 0 0
#> 188 16.16 1 46 0 1
#> 78 23.88 1 43 0 0
#> 23 16.92 1 61 0 0
#> 25 6.32 1 34 1 0
#> 59 10.16 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 149 8.37 1 33 1 0
#> 13.1 14.34 1 54 0 1
#> 63 22.77 1 31 1 0
#> 26.1 15.77 1 49 0 1
#> 153 21.33 1 55 1 0
#> 14 12.89 1 21 0 0
#> 25.1 6.32 1 34 1 0
#> 4 17.64 1 NA 0 1
#> 89 11.44 1 NA 0 0
#> 68 20.62 1 44 0 0
#> 49 12.19 1 48 1 0
#> 190 20.81 1 42 1 0
#> 168 23.72 1 70 0 0
#> 77 7.27 1 67 0 1
#> 183 9.24 1 67 1 0
#> 52 10.42 1 52 0 1
#> 23.1 16.92 1 61 0 0
#> 42 12.43 1 49 0 1
#> 145 10.07 1 65 1 0
#> 139.1 21.49 1 63 1 0
#> 18 15.21 1 49 1 0
#> 155 13.08 1 26 0 0
#> 81 14.06 1 34 0 0
#> 167 15.55 1 56 1 0
#> 88 18.37 1 47 0 0
#> 157 15.10 1 47 0 0
#> 150.2 20.33 1 48 0 0
#> 159 10.55 1 50 0 1
#> 192 16.44 1 31 1 0
#> 41 18.02 1 40 1 0
#> 61 10.12 1 36 0 1
#> 123 13.00 1 44 1 0
#> 195 11.76 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 76 19.22 1 54 0 1
#> 96 14.54 1 33 0 1
#> 96.1 14.54 1 33 0 1
#> 197 21.60 1 69 1 0
#> 52.1 10.42 1 52 0 1
#> 90 20.94 1 50 0 1
#> 93 10.33 1 52 0 1
#> 124 9.73 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 129 23.41 1 53 1 0
#> 114 13.68 1 NA 0 0
#> 106.1 16.67 1 49 1 0
#> 114.1 13.68 1 NA 0 0
#> 4.1 17.64 1 NA 0 1
#> 169 22.41 1 46 0 0
#> 154 12.63 1 20 1 0
#> 158 20.14 1 74 1 0
#> 93.1 10.33 1 52 0 1
#> 167.1 15.55 1 56 1 0
#> 188.1 16.16 1 46 0 1
#> 159.1 10.55 1 50 0 1
#> 49.1 12.19 1 48 1 0
#> 16 8.71 1 71 0 1
#> 183.1 9.24 1 67 1 0
#> 60 13.15 1 38 1 0
#> 93.2 10.33 1 52 0 1
#> 81.1 14.06 1 34 0 0
#> 166 19.98 1 48 0 0
#> 32 20.90 1 37 1 0
#> 55 19.34 1 69 0 1
#> 167.2 15.55 1 56 1 0
#> 179 18.63 1 42 0 0
#> 55.1 19.34 1 69 0 1
#> 150.3 20.33 1 48 0 0
#> 133 14.65 1 57 0 0
#> 106.2 16.67 1 49 1 0
#> 61.1 10.12 1 36 0 1
#> 167.3 15.55 1 56 1 0
#> 107.1 11.18 1 54 1 0
#> 91 5.33 1 61 0 1
#> 133.1 14.65 1 57 0 0
#> 32.1 20.90 1 37 1 0
#> 76.1 19.22 1 54 0 1
#> 167.4 15.55 1 56 1 0
#> 66.1 22.13 1 53 0 0
#> 49.2 12.19 1 48 1 0
#> 154.1 12.63 1 20 1 0
#> 108 18.29 1 39 0 1
#> 139.2 21.49 1 63 1 0
#> 45.1 17.42 1 54 0 1
#> 69 23.23 1 25 0 1
#> 36.1 21.19 1 48 0 1
#> 105.1 19.75 1 60 0 0
#> 134 17.81 1 47 1 0
#> 99 21.19 1 38 0 1
#> 88.1 18.37 1 47 0 0
#> 50 10.02 1 NA 1 0
#> 153.1 21.33 1 55 1 0
#> 48 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 54 24.00 0 53 1 0
#> 122 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 46 24.00 0 71 0 0
#> 173 24.00 0 19 0 1
#> 146.1 24.00 0 63 1 0
#> 47 24.00 0 38 0 1
#> 22 24.00 0 52 1 0
#> 62 24.00 0 71 0 0
#> 20 24.00 0 46 1 0
#> 163 24.00 0 66 0 0
#> 62.1 24.00 0 71 0 0
#> 162 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 172 24.00 0 41 0 0
#> 31 24.00 0 36 0 1
#> 2 24.00 0 9 0 0
#> 71 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 115 24.00 0 NA 1 0
#> 87 24.00 0 27 0 0
#> 84 24.00 0 39 0 1
#> 94 24.00 0 51 0 1
#> 120 24.00 0 68 0 1
#> 174 24.00 0 49 1 0
#> 54.1 24.00 0 53 1 0
#> 62.2 24.00 0 71 0 0
#> 120.1 24.00 0 68 0 1
#> 3 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 73 24.00 0 NA 0 1
#> 132 24.00 0 55 0 0
#> 186 24.00 0 45 1 0
#> 118 24.00 0 44 1 0
#> 22.1 24.00 0 52 1 0
#> 120.2 24.00 0 68 0 1
#> 75 24.00 0 21 1 0
#> 109 24.00 0 48 0 0
#> 172.1 24.00 0 41 0 0
#> 38 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 163.1 24.00 0 66 0 0
#> 74 24.00 0 43 0 1
#> 172.2 24.00 0 41 0 0
#> 2.1 24.00 0 9 0 0
#> 53 24.00 0 32 0 1
#> 163.2 24.00 0 66 0 0
#> 80 24.00 0 41 0 0
#> 146.2 24.00 0 63 1 0
#> 82 24.00 0 34 0 0
#> 27 24.00 0 63 1 0
#> 47.1 24.00 0 38 0 1
#> 53.1 24.00 0 32 0 1
#> 21 24.00 0 47 0 0
#> 2.2 24.00 0 9 0 0
#> 148 24.00 0 61 1 0
#> 152 24.00 0 36 0 1
#> 28.1 24.00 0 67 1 0
#> 20.1 24.00 0 46 1 0
#> 186.1 24.00 0 45 1 0
#> 53.2 24.00 0 32 0 1
#> 103 24.00 0 56 1 0
#> 185 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 54.2 24.00 0 53 1 0
#> 131 24.00 0 66 0 0
#> 12 24.00 0 63 0 0
#> 160 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 38.1 24.00 0 31 1 0
#> 54.3 24.00 0 53 1 0
#> 160.1 24.00 0 31 1 0
#> 47.2 24.00 0 38 0 1
#> 87.1 24.00 0 27 0 0
#> 156 24.00 0 50 1 0
#> 21.1 24.00 0 47 0 0
#> 156.1 24.00 0 50 1 0
#> 75.1 24.00 0 21 1 0
#> 126 24.00 0 48 0 0
#> 48.1 24.00 0 31 1 0
#> 72.1 24.00 0 40 0 1
#> 27.1 24.00 0 63 1 0
#> 19 24.00 0 57 0 1
#> 53.3 24.00 0 32 0 1
#> 191 24.00 0 60 0 1
#> 34 24.00 0 36 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.664 NA NA NA
#> 2 age, Cure model 0.0125 NA NA NA
#> 3 grade_ii, Cure model 0.198 NA NA NA
#> 4 grade_iii, Cure model 0.554 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00562 NA NA NA
#> 2 grade_ii, Survival model 0.407 NA NA NA
#> 3 grade_iii, Survival model 0.448 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.66419 0.01251 0.19781 0.55401
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 256.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.66419280 0.01250875 0.19780965 0.55401038
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005619827 0.407293565 0.447655993
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.30180817 0.17066106 0.38978591 0.01507993 0.55766793 0.24536275
#> [7] 0.32145135 0.81495190 0.68157127 0.08048242 0.12184048 0.24536275
#> [13] 0.45949102 0.09070481 0.53820161 0.00422075 0.47913779 0.97256338
#> [19] 0.37002025 0.95411727 0.68157127 0.05968822 0.55766793 0.15088423
#> [25] 0.74871914 0.97256338 0.23592025 0.78686257 0.22655988 0.02542228
#> [31] 0.96334358 0.92645329 0.85245142 0.47913779 0.77733506 0.91719357
#> [37] 0.12184048 0.62377918 0.72945648 0.70065598 0.57700740 0.39973743
#> [43] 0.63340643 0.24536275 0.83373988 0.52830363 0.42962011 0.89875968
#> [49] 0.73909870 0.44949336 0.35052723 0.66240336 0.66240336 0.11112960
#> [55] 0.85245142 0.19844236 0.87109417 0.49902127 0.03740476 0.49902127
#> [61] 0.06990814 0.75835336 0.28228344 0.87109417 0.57700740 0.53820161
#> [67] 0.83373988 0.78686257 0.94486875 0.92645329 0.71983156 0.87109417
#> [73] 0.70065598 0.29200721 0.20808641 0.32145135 0.57700740 0.37987605
#> [79] 0.32145135 0.24536275 0.64306776 0.49902127 0.89875968 0.57700740
#> [85] 0.81495190 0.99083239 0.64306776 0.20808641 0.35052723 0.57700740
#> [91] 0.09070481 0.78686257 0.75835336 0.41961982 0.12184048 0.45949102
#> [97] 0.04899366 0.17066106 0.30180817 0.43957402 0.17066106 0.39973743
#> [103] 0.15088423 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 105 36 8 86 26 150 58 107 13 194 139 150.1 45
#> 19.75 21.19 18.43 23.81 15.77 20.33 19.34 11.18 14.34 22.40 21.49 20.33 17.42
#> 66 188 78 23 25 97 149 13.1 63 26.1 153 14 25.1
#> 22.13 16.16 23.88 16.92 6.32 19.14 8.37 14.34 22.77 15.77 21.33 12.89 6.32
#> 68 49 190 168 77 183 52 23.1 42 145 139.1 18 155
#> 20.62 12.19 20.81 23.72 7.27 9.24 10.42 16.92 12.43 10.07 21.49 15.21 13.08
#> 81 167 88 157 150.2 159 192 41 61 123 30 76 96
#> 14.06 15.55 18.37 15.10 20.33 10.55 16.44 18.02 10.12 13.00 17.43 19.22 14.54
#> 96.1 197 52.1 90 93 106 129 106.1 169 154 158 93.1 167.1
#> 14.54 21.60 10.42 20.94 10.33 16.67 23.41 16.67 22.41 12.63 20.14 10.33 15.55
#> 188.1 159.1 49.1 16 183.1 60 93.2 81.1 166 32 55 167.2 179
#> 16.16 10.55 12.19 8.71 9.24 13.15 10.33 14.06 19.98 20.90 19.34 15.55 18.63
#> 55.1 150.3 133 106.2 61.1 167.3 107.1 91 133.1 32.1 76.1 167.4 66.1
#> 19.34 20.33 14.65 16.67 10.12 15.55 11.18 5.33 14.65 20.90 19.22 15.55 22.13
#> 49.2 154.1 108 139.2 45.1 69 36.1 105.1 134 99 88.1 153.1 48
#> 12.19 12.63 18.29 21.49 17.42 23.23 21.19 19.75 17.81 21.19 18.37 21.33 24.00
#> 198 54 122 146 46 173 146.1 47 22 62 20 163 62.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 121 172 31 2 71 119 87 84 94 120 174 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.2 120.1 3 28 132 186 118 22.1 120.2 75 109 172.1 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 163.1 74 172.2 2.1 53 163.2 80 146.2 82 27 47.1 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 2.2 148 152 28.1 20.1 186.1 53.2 103 185 72 54.2 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 160 165 38.1 54.3 160.1 47.2 87.1 156 21.1 156.1 75.1 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.1 72.1 27.1 19 53.3 191 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[5]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01016881 0.89541364 0.53576940
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.639789983 0.004486776 0.396017645
#> grade_iii, Cure model
#> 1.593315767
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 42 12.43 1 49 0 1
#> 70 7.38 1 30 1 0
#> 89 11.44 1 NA 0 0
#> 90 20.94 1 50 0 1
#> 88 18.37 1 47 0 0
#> 114 13.68 1 NA 0 0
#> 90.1 20.94 1 50 0 1
#> 108 18.29 1 39 0 1
#> 145 10.07 1 65 1 0
#> 51 18.23 1 83 0 1
#> 37 12.52 1 57 1 0
#> 61 10.12 1 36 0 1
#> 5 16.43 1 51 0 1
#> 60 13.15 1 38 1 0
#> 96 14.54 1 33 0 1
#> 92 22.92 1 47 0 1
#> 60.1 13.15 1 38 1 0
#> 56 12.21 1 60 0 0
#> 140 12.68 1 59 1 0
#> 60.2 13.15 1 38 1 0
#> 169 22.41 1 46 0 0
#> 166 19.98 1 48 0 0
#> 77 7.27 1 67 0 1
#> 190 20.81 1 42 1 0
#> 145.1 10.07 1 65 1 0
#> 123 13.00 1 44 1 0
#> 66 22.13 1 53 0 0
#> 183 9.24 1 67 1 0
#> 43 12.10 1 61 0 1
#> 66.1 22.13 1 53 0 0
#> 96.1 14.54 1 33 0 1
#> 96.2 14.54 1 33 0 1
#> 192 16.44 1 31 1 0
#> 136 21.83 1 43 0 1
#> 195 11.76 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 23 16.92 1 61 0 0
#> 159 10.55 1 50 0 1
#> 42.1 12.43 1 49 0 1
#> 130 16.47 1 53 0 1
#> 36 21.19 1 48 0 1
#> 79 16.23 1 54 1 0
#> 101 9.97 1 10 0 1
#> 153 21.33 1 55 1 0
#> 123.1 13.00 1 44 1 0
#> 88.1 18.37 1 47 0 0
#> 13 14.34 1 54 0 1
#> 188 16.16 1 46 0 1
#> 169.1 22.41 1 46 0 0
#> 175 21.91 1 43 0 0
#> 170 19.54 1 43 0 1
#> 50 10.02 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 41 18.02 1 40 1 0
#> 190.1 20.81 1 42 1 0
#> 140.1 12.68 1 59 1 0
#> 106 16.67 1 49 1 0
#> 188.1 16.16 1 46 0 1
#> 192.1 16.44 1 31 1 0
#> 155 13.08 1 26 0 0
#> 79.1 16.23 1 54 1 0
#> 50.1 10.02 1 NA 1 0
#> 88.2 18.37 1 47 0 0
#> 175.1 21.91 1 43 0 0
#> 8 18.43 1 32 0 0
#> 92.1 22.92 1 47 0 1
#> 175.2 21.91 1 43 0 0
#> 10 10.53 1 34 0 0
#> 40 18.00 1 28 1 0
#> 187 9.92 1 39 1 0
#> 134 17.81 1 47 1 0
#> 58 19.34 1 39 0 0
#> 136.1 21.83 1 43 0 1
#> 134.1 17.81 1 47 1 0
#> 41.1 18.02 1 40 1 0
#> 10.1 10.53 1 34 0 0
#> 37.1 12.52 1 57 1 0
#> 171 16.57 1 41 0 1
#> 159.1 10.55 1 50 0 1
#> 159.2 10.55 1 50 0 1
#> 13.1 14.34 1 54 0 1
#> 89.1 11.44 1 NA 0 0
#> 97 19.14 1 65 0 1
#> 195.1 11.76 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 183.1 9.24 1 67 1 0
#> 177 12.53 1 75 0 0
#> 26.1 15.77 1 49 0 1
#> 77.1 7.27 1 67 0 1
#> 150 20.33 1 48 0 0
#> 36.1 21.19 1 48 0 1
#> 175.3 21.91 1 43 0 0
#> 8.1 18.43 1 32 0 0
#> 91 5.33 1 61 0 1
#> 86 23.81 1 58 0 1
#> 101.1 9.97 1 10 0 1
#> 51.1 18.23 1 83 0 1
#> 110 17.56 1 65 0 1
#> 181 16.46 1 45 0 1
#> 49 12.19 1 48 1 0
#> 59 10.16 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 117 17.46 1 26 0 1
#> 159.3 10.55 1 50 0 1
#> 153.1 21.33 1 55 1 0
#> 49.1 12.19 1 48 1 0
#> 97.1 19.14 1 65 0 1
#> 124 9.73 1 NA 1 0
#> 89.2 11.44 1 NA 0 0
#> 8.2 18.43 1 32 0 0
#> 171.1 16.57 1 41 0 1
#> 139.1 21.49 1 63 1 0
#> 174 24.00 0 49 1 0
#> 21 24.00 0 47 0 0
#> 72 24.00 0 40 0 1
#> 67 24.00 0 25 0 0
#> 54 24.00 0 53 1 0
#> 163 24.00 0 66 0 0
#> 141 24.00 0 44 1 0
#> 174.1 24.00 0 49 1 0
#> 73 24.00 0 NA 0 1
#> 75 24.00 0 21 1 0
#> 44 24.00 0 56 0 0
#> 21.1 24.00 0 47 0 0
#> 84 24.00 0 39 0 1
#> 22 24.00 0 52 1 0
#> 198 24.00 0 66 0 1
#> 28 24.00 0 67 1 0
#> 19 24.00 0 57 0 1
#> 147 24.00 0 76 1 0
#> 186 24.00 0 45 1 0
#> 75.1 24.00 0 21 1 0
#> 38 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 200 24.00 0 64 0 0
#> 137 24.00 0 45 1 0
#> 28.1 24.00 0 67 1 0
#> 118 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 1 24.00 0 23 1 0
#> 196 24.00 0 19 0 0
#> 144 24.00 0 28 0 1
#> 151 24.00 0 42 0 0
#> 172 24.00 0 41 0 0
#> 200.1 24.00 0 64 0 0
#> 103 24.00 0 56 1 0
#> 34.1 24.00 0 36 0 0
#> 11 24.00 0 42 0 1
#> 47 24.00 0 38 0 1
#> 65 24.00 0 57 1 0
#> 12 24.00 0 63 0 0
#> 172.1 24.00 0 41 0 0
#> 151.1 24.00 0 42 0 0
#> 196.1 24.00 0 19 0 0
#> 147.1 24.00 0 76 1 0
#> 98 24.00 0 34 1 0
#> 9 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 73.1 24.00 0 NA 0 1
#> 102 24.00 0 49 0 0
#> 7 24.00 0 37 1 0
#> 34.2 24.00 0 36 0 0
#> 131 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#> 160 24.00 0 31 1 0
#> 12.1 24.00 0 63 0 0
#> 94 24.00 0 51 0 1
#> 94.1 24.00 0 51 0 1
#> 141.1 24.00 0 44 1 0
#> 53 24.00 0 32 0 1
#> 148 24.00 0 61 1 0
#> 185 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 151.2 24.00 0 42 0 0
#> 198.1 24.00 0 66 0 1
#> 98.1 24.00 0 34 1 0
#> 47.1 24.00 0 38 0 1
#> 28.2 24.00 0 67 1 0
#> 98.2 24.00 0 34 1 0
#> 193 24.00 0 45 0 1
#> 109.1 24.00 0 48 0 0
#> 146 24.00 0 63 1 0
#> 165 24.00 0 47 0 0
#> 174.2 24.00 0 49 1 0
#> 1.1 24.00 0 23 1 0
#> 172.2 24.00 0 41 0 0
#> 72.1 24.00 0 40 0 1
#> 80 24.00 0 41 0 0
#> 73.2 24.00 0 NA 0 1
#> 200.2 24.00 0 64 0 0
#> 87 24.00 0 27 0 0
#> 46 24.00 0 71 0 0
#> 148.1 24.00 0 61 1 0
#> 83 24.00 0 6 0 0
#> 102.1 24.00 0 49 0 0
#> 121 24.00 0 57 1 0
#> 122 24.00 0 66 0 0
#> 35 24.00 0 51 0 0
#> 44.1 24.00 0 56 0 0
#> 141.2 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.640 NA NA NA
#> 2 age, Cure model 0.00449 NA NA NA
#> 3 grade_ii, Cure model 0.396 NA NA NA
#> 4 grade_iii, Cure model 1.59 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0102 NA NA NA
#> 2 grade_ii, Survival model 0.895 NA NA NA
#> 3 grade_iii, Survival model 0.536 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.639790 0.004487 0.396018 1.593316
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 239.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.639789983 0.004486776 0.396017645 1.593315767
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01016881 0.89541364 0.53576940
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.783941451 0.964652005 0.193401900 0.336235911 0.193401900 0.368454520
#> [7] 0.901953178 0.379473834 0.765675102 0.892804352 0.566307101 0.682363218
#> [13] 0.634563812 0.014859798 0.682363218 0.802191571 0.738094972 0.682363218
#> [19] 0.028527550 0.243476856 0.973491393 0.213948637 0.901953178 0.719628335
#> [25] 0.045327272 0.946924124 0.829557776 0.045327272 0.634563812 0.634563812
#> [31] 0.546558116 0.107144871 0.453784829 0.484904307 0.838686267 0.783941451
#> [37] 0.526023168 0.172796644 0.576266189 0.920061482 0.152073853 0.719628335
#> [43] 0.336235911 0.663155214 0.595736259 0.028527550 0.065266049 0.253735259
#> [49] 0.274297810 0.401527555 0.213948637 0.738094972 0.495342338 0.595736259
#> [55] 0.546558116 0.710197361 0.576266189 0.336235911 0.065266049 0.305150371
#> [61] 0.014859798 0.065266049 0.874566067 0.422843984 0.937978133 0.433412919
#> [67] 0.263950966 0.107144871 0.433412919 0.401527555 0.874566067 0.765675102
#> [73] 0.505674228 0.838686267 0.838686267 0.663155214 0.284649877 0.615161714
#> [79] 0.946924124 0.756404182 0.615161714 0.973491393 0.233382744 0.172796644
#> [85] 0.065266049 0.305150371 0.991133111 0.005171445 0.920061482 0.379473834
#> [91] 0.464163276 0.536298630 0.811417336 0.130165231 0.474569113 0.838686267
#> [97] 0.152073853 0.811417336 0.284649877 0.305150371 0.505674228 0.130165231
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 42 70 90 88 90.1 108 145 51 37 61 5 60 96
#> 12.43 7.38 20.94 18.37 20.94 18.29 10.07 18.23 12.52 10.12 16.43 13.15 14.54
#> 92 60.1 56 140 60.2 169 166 77 190 145.1 123 66 183
#> 22.92 13.15 12.21 12.68 13.15 22.41 19.98 7.27 20.81 10.07 13.00 22.13 9.24
#> 43 66.1 96.1 96.2 192 136 184 23 159 42.1 130 36 79
#> 12.10 22.13 14.54 14.54 16.44 21.83 17.77 16.92 10.55 12.43 16.47 21.19 16.23
#> 101 153 123.1 88.1 13 188 169.1 175 170 76 41 190.1 140.1
#> 9.97 21.33 13.00 18.37 14.34 16.16 22.41 21.91 19.54 19.22 18.02 20.81 12.68
#> 106 188.1 192.1 155 79.1 88.2 175.1 8 92.1 175.2 10 40 187
#> 16.67 16.16 16.44 13.08 16.23 18.37 21.91 18.43 22.92 21.91 10.53 18.00 9.92
#> 134 58 136.1 134.1 41.1 10.1 37.1 171 159.1 159.2 13.1 97 26
#> 17.81 19.34 21.83 17.81 18.02 10.53 12.52 16.57 10.55 10.55 14.34 19.14 15.77
#> 183.1 177 26.1 77.1 150 36.1 175.3 8.1 91 86 101.1 51.1 110
#> 9.24 12.53 15.77 7.27 20.33 21.19 21.91 18.43 5.33 23.81 9.97 18.23 17.56
#> 181 49 139 117 159.3 153.1 49.1 97.1 8.2 171.1 139.1 174 21
#> 16.46 12.19 21.49 17.46 10.55 21.33 12.19 19.14 18.43 16.57 21.49 24.00 24.00
#> 72 67 54 163 141 174.1 75 44 21.1 84 22 198 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 147 186 75.1 38 34 200 137 28.1 118 109 1 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 151 172 200.1 103 34.1 11 47 65 12 172.1 151.1 196.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147.1 98 9 143 102 7 34.2 131 132 160 12.1 94 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.1 53 148 185 33 151.2 198.1 98.1 47.1 28.2 98.2 193 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 165 174.2 1.1 172.2 72.1 80 200.2 87 46 148.1 83 102.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 122 35 44.1 141.2
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[6]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005618887 0.681939416 0.385878864
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.21631853 0.02222606 0.40376135
#> grade_iii, Cure model
#> 0.82537701
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 85 16.44 1 36 0 0
#> 184 17.77 1 38 0 0
#> 76 19.22 1 54 0 1
#> 61 10.12 1 36 0 1
#> 105 19.75 1 60 0 0
#> 107 11.18 1 54 1 0
#> 68 20.62 1 44 0 0
#> 6 15.64 1 39 0 0
#> 16 8.71 1 71 0 1
#> 77 7.27 1 67 0 1
#> 180 14.82 1 37 0 0
#> 164 23.60 1 76 0 1
#> 188 16.16 1 46 0 1
#> 58 19.34 1 39 0 0
#> 192 16.44 1 31 1 0
#> 105.1 19.75 1 60 0 0
#> 51 18.23 1 83 0 1
#> 150 20.33 1 48 0 0
#> 40 18.00 1 28 1 0
#> 157 15.10 1 47 0 0
#> 100 16.07 1 60 0 0
#> 49 12.19 1 48 1 0
#> 183 9.24 1 67 1 0
#> 59 10.16 1 NA 1 0
#> 32 20.90 1 37 1 0
#> 61.1 10.12 1 36 0 1
#> 26 15.77 1 49 0 1
#> 96 14.54 1 33 0 1
#> 199 19.81 1 NA 0 1
#> 140 12.68 1 59 1 0
#> 49.1 12.19 1 48 1 0
#> 100.1 16.07 1 60 0 0
#> 169 22.41 1 46 0 0
#> 190 20.81 1 42 1 0
#> 42 12.43 1 49 0 1
#> 24 23.89 1 38 0 0
#> 30 17.43 1 78 0 0
#> 29 15.45 1 68 1 0
#> 101 9.97 1 10 0 1
#> 158 20.14 1 74 1 0
#> 127 3.53 1 62 0 1
#> 63 22.77 1 31 1 0
#> 114 13.68 1 NA 0 0
#> 123 13.00 1 44 1 0
#> 36 21.19 1 48 0 1
#> 85.1 16.44 1 36 0 0
#> 51.1 18.23 1 83 0 1
#> 26.1 15.77 1 49 0 1
#> 113 22.86 1 34 0 0
#> 101.1 9.97 1 10 0 1
#> 140.1 12.68 1 59 1 0
#> 70 7.38 1 30 1 0
#> 199.1 19.81 1 NA 0 1
#> 167 15.55 1 56 1 0
#> 168 23.72 1 70 0 0
#> 149 8.37 1 33 1 0
#> 124 9.73 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 76.1 19.22 1 54 0 1
#> 8 18.43 1 32 0 0
#> 66 22.13 1 53 0 0
#> 113.1 22.86 1 34 0 0
#> 45 17.42 1 54 0 1
#> 158.1 20.14 1 74 1 0
#> 194 22.40 1 38 0 1
#> 106 16.67 1 49 1 0
#> 93 10.33 1 52 0 1
#> 57 14.46 1 45 0 1
#> 39 15.59 1 37 0 1
#> 183.1 9.24 1 67 1 0
#> 6.1 15.64 1 39 0 0
#> 171 16.57 1 41 0 1
#> 130 16.47 1 53 0 1
#> 139 21.49 1 63 1 0
#> 89 11.44 1 NA 0 0
#> 158.2 20.14 1 74 1 0
#> 149.1 8.37 1 33 1 0
#> 197 21.60 1 69 1 0
#> 36.1 21.19 1 48 0 1
#> 52 10.42 1 52 0 1
#> 14 12.89 1 21 0 0
#> 127.1 3.53 1 62 0 1
#> 68.1 20.62 1 44 0 0
#> 169.1 22.41 1 46 0 0
#> 92 22.92 1 47 0 1
#> 37 12.52 1 57 1 0
#> 10 10.53 1 34 0 0
#> 86 23.81 1 58 0 1
#> 113.2 22.86 1 34 0 0
#> 23 16.92 1 61 0 0
#> 57.1 14.46 1 45 0 1
#> 50 10.02 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 41 18.02 1 40 1 0
#> 183.2 9.24 1 67 1 0
#> 145 10.07 1 65 1 0
#> 155 13.08 1 26 0 0
#> 117 17.46 1 26 0 1
#> 145.1 10.07 1 65 1 0
#> 10.1 10.53 1 34 0 0
#> 136 21.83 1 43 0 1
#> 92.1 22.92 1 47 0 1
#> 189 10.51 1 NA 1 0
#> 6.2 15.64 1 39 0 0
#> 130.1 16.47 1 53 0 1
#> 16.1 8.71 1 71 0 1
#> 40.1 18.00 1 28 1 0
#> 197.1 21.60 1 69 1 0
#> 175 21.91 1 43 0 0
#> 169.2 22.41 1 46 0 0
#> 192.1 16.44 1 31 1 0
#> 76.2 19.22 1 54 0 1
#> 71 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 47 24.00 0 38 0 1
#> 131 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 71.1 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 28 24.00 0 67 1 0
#> 156 24.00 0 50 1 0
#> 148 24.00 0 61 1 0
#> 48 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 165 24.00 0 47 0 0
#> 80.1 24.00 0 41 0 0
#> 109 24.00 0 48 0 0
#> 74 24.00 0 43 0 1
#> 28.1 24.00 0 67 1 0
#> 135 24.00 0 58 1 0
#> 162 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 200 24.00 0 64 0 0
#> 65 24.00 0 57 1 0
#> 165.1 24.00 0 47 0 0
#> 103 24.00 0 56 1 0
#> 44 24.00 0 56 0 0
#> 75 24.00 0 21 1 0
#> 38 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 151.1 24.00 0 42 0 0
#> 53 24.00 0 32 0 1
#> 165.2 24.00 0 47 0 0
#> 165.3 24.00 0 47 0 0
#> 178 24.00 0 52 1 0
#> 48.1 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 143 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 53.1 24.00 0 32 0 1
#> 162.1 24.00 0 51 0 0
#> 75.1 24.00 0 21 1 0
#> 65.1 24.00 0 57 1 0
#> 161.1 24.00 0 45 0 0
#> 103.1 24.00 0 56 1 0
#> 20 24.00 0 46 1 0
#> 67 24.00 0 25 0 0
#> 118 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 151.2 24.00 0 42 0 0
#> 67.1 24.00 0 25 0 0
#> 163 24.00 0 66 0 0
#> 74.1 24.00 0 43 0 1
#> 196 24.00 0 19 0 0
#> 64 24.00 0 43 0 0
#> 3 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 126 24.00 0 48 0 0
#> 83 24.00 0 6 0 0
#> 182 24.00 0 35 0 0
#> 3.1 24.00 0 31 1 0
#> 84.1 24.00 0 39 0 1
#> 87 24.00 0 27 0 0
#> 11 24.00 0 42 0 1
#> 104 24.00 0 50 1 0
#> 191.1 24.00 0 60 0 1
#> 48.2 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 47.1 24.00 0 38 0 1
#> 46 24.00 0 71 0 0
#> 182.1 24.00 0 35 0 0
#> 109.1 24.00 0 48 0 0
#> 72 24.00 0 40 0 1
#> 31 24.00 0 36 0 1
#> 162.2 24.00 0 51 0 0
#> 64.1 24.00 0 43 0 0
#> 38.1 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 115 24.00 0 NA 1 0
#> 33 24.00 0 53 0 0
#> 72.1 24.00 0 40 0 1
#> 38.2 24.00 0 31 1 0
#> 74.2 24.00 0 43 0 1
#> 191.2 24.00 0 60 0 1
#> 98 24.00 0 34 1 0
#> 82 24.00 0 34 0 0
#> 161.2 24.00 0 45 0 0
#> 131.1 24.00 0 66 0 0
#> 131.2 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.22 NA NA NA
#> 2 age, Cure model 0.0222 NA NA NA
#> 3 grade_ii, Cure model 0.404 NA NA NA
#> 4 grade_iii, Cure model 0.825 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00562 NA NA NA
#> 2 grade_ii, Survival model 0.682 NA NA NA
#> 3 grade_iii, Survival model 0.386 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.21632 0.02223 0.40376 0.82538
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 252.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.21631853 0.02222606 0.40376135 0.82537701
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005618887 0.681939416 0.385878864
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.53146209 0.44562188 0.35813442 0.85253388 0.32848699 0.80770093
#> [7] 0.25991179 0.61421699 0.93138003 0.97441718 0.67936232 0.03722415
#> [13] 0.56779654 0.34811939 0.53146209 0.32848699 0.39710962 0.28983464
#> [19] 0.42672453 0.67004961 0.57708595 0.78977933 0.90549647 0.23975246
#> [25] 0.85253388 0.59568526 0.68869905 0.74418087 0.78977933 0.57708595
#> [31] 0.11153913 0.24994628 0.78066096 0.00426747 0.46474855 0.66076684
#> [37] 0.88797776 0.29996356 0.98297337 0.10082590 0.72571996 0.21928206
#> [43] 0.53146209 0.39710962 0.59568526 0.07006185 0.88797776 0.74418087
#> [49] 0.96586028 0.65143826 0.02512674 0.94872086 0.76235194 0.35813442
#> [55] 0.38714519 0.15361752 0.07006185 0.47435462 0.29996356 0.14257699
#> [61] 0.49358885 0.84355446 0.69800778 0.64205001 0.90549647 0.61421699
#> [67] 0.50314007 0.51266089 0.20867191 0.29996356 0.94872086 0.18758616
#> [73] 0.21928206 0.83456564 0.73494396 0.98297337 0.25991179 0.11153913
#> [79] 0.04951829 0.77153011 0.81666598 0.01471764 0.07006185 0.48394401
#> [85] 0.69800778 0.27978874 0.41686434 0.90549647 0.87032304 0.71643167
#> [91] 0.45521243 0.87032304 0.81666598 0.17628301 0.04951829 0.61421699
#> [97] 0.51266089 0.93138003 0.42672453 0.18758616 0.16486655 0.11153913
#> [103] 0.53146209 0.35813442 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 85 184 76 61 105 107 68 6 16 77 180 164 188
#> 16.44 17.77 19.22 10.12 19.75 11.18 20.62 15.64 8.71 7.27 14.82 23.60 16.16
#> 58 192 105.1 51 150 40 157 100 49 183 32 61.1 26
#> 19.34 16.44 19.75 18.23 20.33 18.00 15.10 16.07 12.19 9.24 20.90 10.12 15.77
#> 96 140 49.1 100.1 169 190 42 24 30 29 101 158 127
#> 14.54 12.68 12.19 16.07 22.41 20.81 12.43 23.89 17.43 15.45 9.97 20.14 3.53
#> 63 123 36 85.1 51.1 26.1 113 101.1 140.1 70 167 168 149
#> 22.77 13.00 21.19 16.44 18.23 15.77 22.86 9.97 12.68 7.38 15.55 23.72 8.37
#> 177 76.1 8 66 113.1 45 158.1 194 106 93 57 39 183.1
#> 12.53 19.22 18.43 22.13 22.86 17.42 20.14 22.40 16.67 10.33 14.46 15.59 9.24
#> 6.1 171 130 139 158.2 149.1 197 36.1 52 14 127.1 68.1 169.1
#> 15.64 16.57 16.47 21.49 20.14 8.37 21.60 21.19 10.42 12.89 3.53 20.62 22.41
#> 92 37 10 86 113.2 23 57.1 128 41 183.2 145 155 117
#> 22.92 12.52 10.53 23.81 22.86 16.92 14.46 20.35 18.02 9.24 10.07 13.08 17.46
#> 145.1 10.1 136 92.1 6.2 130.1 16.1 40.1 197.1 175 169.2 192.1 76.2
#> 10.07 10.53 21.83 22.92 15.64 16.47 8.71 18.00 21.60 21.91 22.41 16.44 19.22
#> 71 151 47 131 84 71.1 119 28 156 148 48 35 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 80.1 109 74 28.1 135 162 161 200 65 165.1 103 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 38 9 151.1 53 165.2 165.3 178 48.1 193 143 191 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.1 75.1 65.1 161.1 103.1 20 67 118 144 151.2 67.1 163 74.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 64 3 172 126 83 182 3.1 84.1 87 11 104 191.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.2 198 47.1 46 182.1 109.1 72 31 162.2 64.1 38.1 152 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 38.2 74.2 191.2 98 82 161.2 131.1 131.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[7]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001439673 0.792027491 0.482593500
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.659496554 0.001593928 0.642704347
#> grade_iii, Cure model
#> 1.519519386
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 90 20.94 1 50 0 1
#> 90.1 20.94 1 50 0 1
#> 129 23.41 1 53 1 0
#> 189 10.51 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 42 12.43 1 49 0 1
#> 56 12.21 1 60 0 0
#> 49 12.19 1 48 1 0
#> 106 16.67 1 49 1 0
#> 16 8.71 1 71 0 1
#> 32 20.90 1 37 1 0
#> 199 19.81 1 NA 0 1
#> 18 15.21 1 49 1 0
#> 79 16.23 1 54 1 0
#> 105 19.75 1 60 0 0
#> 106.1 16.67 1 49 1 0
#> 56.1 12.21 1 60 0 0
#> 5 16.43 1 51 0 1
#> 111 17.45 1 47 0 1
#> 117 17.46 1 26 0 1
#> 51 18.23 1 83 0 1
#> 134 17.81 1 47 1 0
#> 99 21.19 1 38 0 1
#> 57 14.46 1 45 0 1
#> 101 9.97 1 10 0 1
#> 45 17.42 1 54 0 1
#> 50 10.02 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 195 11.76 1 NA 1 0
#> 106.2 16.67 1 49 1 0
#> 127 3.53 1 62 0 1
#> 187 9.92 1 39 1 0
#> 101.1 9.97 1 10 0 1
#> 85 16.44 1 36 0 0
#> 194 22.40 1 38 0 1
#> 56.2 12.21 1 60 0 0
#> 78 23.88 1 43 0 0
#> 129.1 23.41 1 53 1 0
#> 40 18.00 1 28 1 0
#> 175 21.91 1 43 0 0
#> 79.1 16.23 1 54 1 0
#> 60 13.15 1 38 1 0
#> 29 15.45 1 68 1 0
#> 124 9.73 1 NA 1 0
#> 29.1 15.45 1 68 1 0
#> 183 9.24 1 67 1 0
#> 181 16.46 1 45 0 1
#> 49.1 12.19 1 48 1 0
#> 50.1 10.02 1 NA 1 0
#> 45.1 17.42 1 54 0 1
#> 166 19.98 1 48 0 0
#> 199.1 19.81 1 NA 0 1
#> 128 20.35 1 35 0 1
#> 181.1 16.46 1 45 0 1
#> 25 6.32 1 34 1 0
#> 66 22.13 1 53 0 0
#> 127.1 3.53 1 62 0 1
#> 50.2 10.02 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 108 18.29 1 39 0 1
#> 125 15.65 1 67 1 0
#> 184 17.77 1 38 0 0
#> 91 5.33 1 61 0 1
#> 170 19.54 1 43 0 1
#> 81 14.06 1 34 0 0
#> 192 16.44 1 31 1 0
#> 70 7.38 1 30 1 0
#> 16.1 8.71 1 71 0 1
#> 145 10.07 1 65 1 0
#> 171 16.57 1 41 0 1
#> 76 19.22 1 54 0 1
#> 50.3 10.02 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 168 23.72 1 70 0 0
#> 128.1 20.35 1 35 0 1
#> 77 7.27 1 67 0 1
#> 181.2 16.46 1 45 0 1
#> 125.1 15.65 1 67 1 0
#> 14 12.89 1 21 0 0
#> 154 12.63 1 20 1 0
#> 110 17.56 1 65 0 1
#> 37 12.52 1 57 1 0
#> 183.1 9.24 1 67 1 0
#> 114 13.68 1 NA 0 0
#> 170.1 19.54 1 43 0 1
#> 70.1 7.38 1 30 1 0
#> 59 10.16 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 77.1 7.27 1 67 0 1
#> 192.1 16.44 1 31 1 0
#> 184.1 17.77 1 38 0 0
#> 92 22.92 1 47 0 1
#> 49.2 12.19 1 48 1 0
#> 43 12.10 1 61 0 1
#> 60.1 13.15 1 38 1 0
#> 199.2 19.81 1 NA 0 1
#> 13 14.34 1 54 0 1
#> 29.2 15.45 1 68 1 0
#> 139 21.49 1 63 1 0
#> 199.3 19.81 1 NA 0 1
#> 8 18.43 1 32 0 0
#> 111.1 17.45 1 47 0 1
#> 14.1 12.89 1 21 0 0
#> 50.4 10.02 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 70.2 7.38 1 30 1 0
#> 154.1 12.63 1 20 1 0
#> 26 15.77 1 49 0 1
#> 90.2 20.94 1 50 0 1
#> 100 16.07 1 60 0 0
#> 4 17.64 1 NA 0 1
#> 45.2 17.42 1 54 0 1
#> 71 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 95 24.00 0 68 0 1
#> 198 24.00 0 66 0 1
#> 12 24.00 0 63 0 0
#> 98 24.00 0 34 1 0
#> 2 24.00 0 9 0 0
#> 196 24.00 0 19 0 0
#> 95.1 24.00 0 68 0 1
#> 182 24.00 0 35 0 0
#> 102 24.00 0 49 0 0
#> 3 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 109 24.00 0 48 0 0
#> 87 24.00 0 27 0 0
#> 172 24.00 0 41 0 0
#> 83 24.00 0 6 0 0
#> 20 24.00 0 46 1 0
#> 160 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 116 24.00 0 58 0 1
#> 35 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#> 200 24.00 0 64 0 0
#> 178 24.00 0 52 1 0
#> 116.1 24.00 0 58 0 1
#> 193.1 24.00 0 45 0 1
#> 147 24.00 0 76 1 0
#> 162 24.00 0 51 0 0
#> 172.1 24.00 0 41 0 0
#> 35.1 24.00 0 51 0 0
#> 186.1 24.00 0 45 1 0
#> 75 24.00 0 21 1 0
#> 126 24.00 0 48 0 0
#> 72 24.00 0 40 0 1
#> 71.1 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 27 24.00 0 63 1 0
#> 174 24.00 0 49 1 0
#> 182.1 24.00 0 35 0 0
#> 62 24.00 0 71 0 0
#> 48 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 172.2 24.00 0 41 0 0
#> 148 24.00 0 61 1 0
#> 80 24.00 0 41 0 0
#> 152 24.00 0 36 0 1
#> 7 24.00 0 37 1 0
#> 48.1 24.00 0 31 1 0
#> 80.1 24.00 0 41 0 0
#> 94 24.00 0 51 0 1
#> 1 24.00 0 23 1 0
#> 176.1 24.00 0 43 0 1
#> 20.1 24.00 0 46 1 0
#> 62.1 24.00 0 71 0 0
#> 21 24.00 0 47 0 0
#> 198.1 24.00 0 66 0 1
#> 9 24.00 0 31 1 0
#> 160.1 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 119 24.00 0 17 0 0
#> 82 24.00 0 34 0 0
#> 1.1 24.00 0 23 1 0
#> 138 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 62.2 24.00 0 71 0 0
#> 143 24.00 0 51 0 0
#> 178.1 24.00 0 52 1 0
#> 2.1 24.00 0 9 0 0
#> 147.1 24.00 0 76 1 0
#> 95.2 24.00 0 68 0 1
#> 162.1 24.00 0 51 0 0
#> 148.1 24.00 0 61 1 0
#> 137 24.00 0 45 1 0
#> 122 24.00 0 66 0 0
#> 135.1 24.00 0 58 1 0
#> 176.2 24.00 0 43 0 1
#> 103 24.00 0 56 1 0
#> 198.2 24.00 0 66 0 1
#> 141 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 62.3 24.00 0 71 0 0
#> 82.1 24.00 0 34 0 0
#> 122.1 24.00 0 66 0 0
#> 115.1 24.00 0 NA 1 0
#> 48.2 24.00 0 31 1 0
#> 160.2 24.00 0 31 1 0
#> 87.1 24.00 0 27 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.659 NA NA NA
#> 2 age, Cure model 0.00159 NA NA NA
#> 3 grade_ii, Cure model 0.643 NA NA NA
#> 4 grade_iii, Cure model 1.52 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00144 NA NA NA
#> 2 grade_ii, Survival model 0.792 NA NA NA
#> 3 grade_iii, Survival model 0.483 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.659497 0.001594 0.642704 1.519519
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 253
#> Residual Deviance: 237.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.659496554 0.001593928 0.642704347 1.519519386
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001439673 0.792027491 0.482593500
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.23730122 0.23730122 0.08676863 0.79243585 0.82215003 0.82946971
#> [7] 0.85128293 0.55721324 0.92803694 0.27600245 0.73052863 0.65631217
#> [13] 0.33826734 0.55721324 0.82946971 0.64753581 0.50745747 0.49695609
#> [19] 0.43206864 0.45437023 0.22231945 0.73843758 0.89373134 0.52781428
#> [25] 0.87962798 0.55721324 0.98716356 0.90759326 0.89373134 0.62138525
#> [31] 0.15660511 0.82946971 0.01741122 0.08676863 0.44337652 0.18995481
#> [37] 0.65631217 0.76195494 0.70678890 0.70678890 0.91449337 0.59441298
#> [43] 0.85128293 0.52781428 0.32592483 0.30176721 0.59441298 0.97418285
#> [49] 0.17322042 0.98716356 0.39743105 0.42062972 0.69031497 0.46508819
#> [55] 0.98068360 0.35064727 0.75412695 0.62138525 0.94148965 0.92803694
#> [61] 0.88670800 0.58505924 0.37411948 0.38585895 0.05044971 0.30176721
#> [67] 0.96112903 0.59441298 0.69031497 0.77719094 0.80001996 0.48632880
#> [73] 0.81479697 0.91449337 0.35064727 0.94148965 0.28886715 0.96112903
#> [79] 0.62138525 0.46508819 0.12153521 0.85128293 0.87251917 0.76195494
#> [85] 0.74630284 0.70678890 0.20677907 0.40902296 0.50745747 0.77719094
#> [91] 0.13899493 0.94148965 0.80001996 0.68182343 0.23730122 0.67327761
#> [97] 0.52781428 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 90 90.1 129 140 42 56 49 106 16 32 18 79 105
#> 20.94 20.94 23.41 12.68 12.43 12.21 12.19 16.67 8.71 20.90 15.21 16.23 19.75
#> 106.1 56.1 5 111 117 51 134 99 57 101 45 52 106.2
#> 16.67 12.21 16.43 17.45 17.46 18.23 17.81 21.19 14.46 9.97 17.42 10.42 16.67
#> 127 187 101.1 85 194 56.2 78 129.1 40 175 79.1 60 29
#> 3.53 9.92 9.97 16.44 22.40 12.21 23.88 23.41 18.00 21.91 16.23 13.15 15.45
#> 29.1 183 181 49.1 45.1 166 128 181.1 25 66 127.1 179 108
#> 15.45 9.24 16.46 12.19 17.42 19.98 20.35 16.46 6.32 22.13 3.53 18.63 18.29
#> 125 184 91 170 81 192 70 16.1 145 171 76 97 168
#> 15.65 17.77 5.33 19.54 14.06 16.44 7.38 8.71 10.07 16.57 19.22 19.14 23.72
#> 128.1 77 181.2 125.1 14 154 110 37 183.1 170.1 70.1 68 77.1
#> 20.35 7.27 16.46 15.65 12.89 12.63 17.56 12.52 9.24 19.54 7.38 20.62 7.27
#> 192.1 184.1 92 49.2 43 60.1 13 29.2 139 8 111.1 14.1 15
#> 16.44 17.77 22.92 12.19 12.10 13.15 14.34 15.45 21.49 18.43 17.45 12.89 22.68
#> 70.2 154.1 26 90.2 100 45.2 71 44 95 198 12 98 2
#> 7.38 12.63 15.77 20.94 16.07 17.42 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 95.1 182 102 3 193 109 87 172 83 20 160 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 35 176 200 178 116.1 193.1 147 162 172.1 35.1 186.1 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 72 71.1 54 27 174 182.1 62 48 65 172.2 148 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 7 48.1 80.1 94 1 176.1 20.1 62.1 21 198.1 9 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 119 82 1.1 138 135 62.2 143 178.1 2.1 147.1 95.2 162.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.1 137 122 135.1 176.2 103 198.2 141 62.3 82.1 122.1 48.2 160.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[8]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.008527699 0.603936881 0.489038774
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.87743654 0.01495671 0.19480614
#> grade_iii, Cure model
#> 0.82683636
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 153 21.33 1 55 1 0
#> 171 16.57 1 41 0 1
#> 129 23.41 1 53 1 0
#> 150 20.33 1 48 0 0
#> 37 12.52 1 57 1 0
#> 78 23.88 1 43 0 0
#> 10 10.53 1 34 0 0
#> 134 17.81 1 47 1 0
#> 56 12.21 1 60 0 0
#> 45 17.42 1 54 0 1
#> 4 17.64 1 NA 0 1
#> 77 7.27 1 67 0 1
#> 154 12.63 1 20 1 0
#> 127 3.53 1 62 0 1
#> 117 17.46 1 26 0 1
#> 149 8.37 1 33 1 0
#> 159 10.55 1 50 0 1
#> 66 22.13 1 53 0 0
#> 77.1 7.27 1 67 0 1
#> 189 10.51 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 184 17.77 1 38 0 0
#> 195 11.76 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 124 9.73 1 NA 1 0
#> 14 12.89 1 21 0 0
#> 199 19.81 1 NA 0 1
#> 128 20.35 1 35 0 1
#> 107 11.18 1 54 1 0
#> 166 19.98 1 48 0 0
#> 8 18.43 1 32 0 0
#> 130 16.47 1 53 0 1
#> 59 10.16 1 NA 1 0
#> 153.1 21.33 1 55 1 0
#> 199.1 19.81 1 NA 0 1
#> 167.1 15.55 1 56 1 0
#> 49 12.19 1 48 1 0
#> 96 14.54 1 33 0 1
#> 56.1 12.21 1 60 0 0
#> 177 12.53 1 75 0 0
#> 100 16.07 1 60 0 0
#> 37.1 12.52 1 57 1 0
#> 29 15.45 1 68 1 0
#> 187 9.92 1 39 1 0
#> 145 10.07 1 65 1 0
#> 167.2 15.55 1 56 1 0
#> 169 22.41 1 46 0 0
#> 189.1 10.51 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 77.2 7.27 1 67 0 1
#> 99 21.19 1 38 0 1
#> 8.1 18.43 1 32 0 0
#> 55 19.34 1 69 0 1
#> 15.1 22.68 1 48 0 0
#> 78.1 23.88 1 43 0 0
#> 15.2 22.68 1 48 0 0
#> 8.2 18.43 1 32 0 0
#> 86 23.81 1 58 0 1
#> 60.1 13.15 1 38 1 0
#> 159.1 10.55 1 50 0 1
#> 56.2 12.21 1 60 0 0
#> 30 17.43 1 78 0 0
#> 180 14.82 1 37 0 0
#> 14.1 12.89 1 21 0 0
#> 66.1 22.13 1 53 0 0
#> 23 16.92 1 61 0 0
#> 159.2 10.55 1 50 0 1
#> 66.2 22.13 1 53 0 0
#> 36 21.19 1 48 0 1
#> 69 23.23 1 25 0 1
#> 171.1 16.57 1 41 0 1
#> 25 6.32 1 34 1 0
#> 16 8.71 1 71 0 1
#> 124.1 9.73 1 NA 1 0
#> 187.1 9.92 1 39 1 0
#> 23.1 16.92 1 61 0 0
#> 85 16.44 1 36 0 0
#> 199.2 19.81 1 NA 0 1
#> 63 22.77 1 31 1 0
#> 158 20.14 1 74 1 0
#> 23.2 16.92 1 61 0 0
#> 117.1 17.46 1 26 0 1
#> 16.1 8.71 1 71 0 1
#> 55.1 19.34 1 69 0 1
#> 189.2 10.51 1 NA 1 0
#> 69.1 23.23 1 25 0 1
#> 68 20.62 1 44 0 0
#> 114 13.68 1 NA 0 0
#> 188 16.16 1 46 0 1
#> 159.3 10.55 1 50 0 1
#> 5 16.43 1 51 0 1
#> 41 18.02 1 40 1 0
#> 117.2 17.46 1 26 0 1
#> 125 15.65 1 67 1 0
#> 89 11.44 1 NA 0 0
#> 181 16.46 1 45 0 1
#> 169.1 22.41 1 46 0 0
#> 101 9.97 1 10 0 1
#> 168 23.72 1 70 0 0
#> 76 19.22 1 54 0 1
#> 89.1 11.44 1 NA 0 0
#> 60.2 13.15 1 38 1 0
#> 69.2 23.23 1 25 0 1
#> 105 19.75 1 60 0 0
#> 158.1 20.14 1 74 1 0
#> 199.3 19.81 1 NA 0 1
#> 177.1 12.53 1 75 0 0
#> 158.2 20.14 1 74 1 0
#> 113 22.86 1 34 0 0
#> 18 15.21 1 49 1 0
#> 170 19.54 1 43 0 1
#> 130.1 16.47 1 53 0 1
#> 71 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 71.1 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 163 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 132 24.00 0 55 0 0
#> 17 24.00 0 38 0 1
#> 162 24.00 0 51 0 0
#> 71.2 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 20 24.00 0 46 1 0
#> 3 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 172 24.00 0 41 0 0
#> 82 24.00 0 34 0 0
#> 48 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 152 24.00 0 36 0 1
#> 75 24.00 0 21 1 0
#> 82.1 24.00 0 34 0 0
#> 131.1 24.00 0 66 0 0
#> 80 24.00 0 41 0 0
#> 118 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 9 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 182 24.00 0 35 0 0
#> 147 24.00 0 76 1 0
#> 82.2 24.00 0 34 0 0
#> 82.3 24.00 0 34 0 0
#> 98 24.00 0 34 1 0
#> 98.1 24.00 0 34 1 0
#> 178 24.00 0 52 1 0
#> 109.1 24.00 0 48 0 0
#> 143 24.00 0 51 0 0
#> 182.1 24.00 0 35 0 0
#> 200 24.00 0 64 0 0
#> 98.2 24.00 0 34 1 0
#> 73 24.00 0 NA 0 1
#> 156 24.00 0 50 1 0
#> 193 24.00 0 45 0 1
#> 112 24.00 0 61 0 0
#> 104.1 24.00 0 50 1 0
#> 31 24.00 0 36 0 1
#> 115 24.00 0 NA 1 0
#> 144 24.00 0 28 0 1
#> 71.3 24.00 0 51 0 0
#> 147.1 24.00 0 76 1 0
#> 27 24.00 0 63 1 0
#> 138.1 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 193.1 24.00 0 45 0 1
#> 47 24.00 0 38 0 1
#> 156.1 24.00 0 50 1 0
#> 33 24.00 0 53 0 0
#> 120 24.00 0 68 0 1
#> 142 24.00 0 53 0 0
#> 46 24.00 0 71 0 0
#> 135 24.00 0 58 1 0
#> 162.1 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 67 24.00 0 25 0 0
#> 143.1 24.00 0 51 0 0
#> 67.1 24.00 0 25 0 0
#> 44 24.00 0 56 0 0
#> 44.1 24.00 0 56 0 0
#> 116 24.00 0 58 0 1
#> 165 24.00 0 47 0 0
#> 178.1 24.00 0 52 1 0
#> 80.1 24.00 0 41 0 0
#> 185 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 196 24.00 0 19 0 0
#> 176 24.00 0 43 0 1
#> 165.1 24.00 0 47 0 0
#> 82.4 24.00 0 34 0 0
#> 72 24.00 0 40 0 1
#> 72.1 24.00 0 40 0 1
#> 17.1 24.00 0 38 0 1
#> 2 24.00 0 9 0 0
#> 152.1 24.00 0 36 0 1
#> 135.1 24.00 0 58 1 0
#> 12 24.00 0 63 0 0
#> 7.1 24.00 0 37 1 0
#> 54 24.00 0 53 1 0
#> 102 24.00 0 49 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.877 NA NA NA
#> 2 age, Cure model 0.0150 NA NA NA
#> 3 grade_ii, Cure model 0.195 NA NA NA
#> 4 grade_iii, Cure model 0.827 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00853 NA NA NA
#> 2 grade_ii, Survival model 0.604 NA NA NA
#> 3 grade_iii, Survival model 0.489 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.87744 0.01496 0.19481 0.82684
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 253
#> Residual Deviance: 246.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.87743654 0.01495671 0.19480614 0.82683636
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.008527699 0.603936881 0.489038774
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.45263524 0.72373313 0.23018058 0.52245005 0.87934308 0.08396703
#> [7] 0.93728778 0.64821740 0.89025251 0.69456458 0.97678055 0.86248424
#> [13] 0.99539229 0.66418909 0.97197246 0.91700702 0.41238997 0.97678055
#> [19] 0.83399418 0.65622184 0.79166776 0.85108315 0.51131775 0.91171754
#> [25] 0.56165798 0.61532206 0.73789943 0.45263524 0.79166776 0.90636912
#> [31] 0.82807162 0.89025251 0.86815973 0.77860969 0.87934308 0.81004376
#> [37] 0.95245525 0.94239028 0.79166776 0.38346595 0.33934400 0.97678055
#> [43] 0.47705299 0.61532206 0.58968460 0.33934400 0.08396703 0.33934400
#> [49] 0.61532206 0.16791332 0.83399418 0.91700702 0.89025251 0.68696676
#> [55] 0.82209948 0.85108315 0.41238997 0.70203296 0.91700702 0.41238997
#> [61] 0.47705299 0.25376625 0.72373313 0.99074658 0.96231220 0.95245525
#> [67] 0.70203296 0.75847441 0.32281428 0.53346366 0.70203296 0.66418909
#> [73] 0.96231220 0.58968460 0.25376625 0.49988736 0.77198241 0.91700702
#> [79] 0.76527368 0.64003811 0.66418909 0.78519950 0.75165316 0.38346595
#> [85] 0.94743313 0.20099923 0.60686251 0.83399418 0.25376625 0.57113628
#> [91] 0.53346366 0.86815973 0.53346366 0.30502546 0.81611120 0.58051066
#> [97] 0.73789943 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 153 171 129 150 37 78 10 134 56 45 77 154 127
#> 21.33 16.57 23.41 20.33 12.52 23.88 10.53 17.81 12.21 17.42 7.27 12.63 3.53
#> 117 149 159 66 77.1 60 184 167 14 128 107 166 8
#> 17.46 8.37 10.55 22.13 7.27 13.15 17.77 15.55 12.89 20.35 11.18 19.98 18.43
#> 130 153.1 167.1 49 96 56.1 177 100 37.1 29 187 145 167.2
#> 16.47 21.33 15.55 12.19 14.54 12.21 12.53 16.07 12.52 15.45 9.92 10.07 15.55
#> 169 15 77.2 99 8.1 55 15.1 78.1 15.2 8.2 86 60.1 159.1
#> 22.41 22.68 7.27 21.19 18.43 19.34 22.68 23.88 22.68 18.43 23.81 13.15 10.55
#> 56.2 30 180 14.1 66.1 23 159.2 66.2 36 69 171.1 25 16
#> 12.21 17.43 14.82 12.89 22.13 16.92 10.55 22.13 21.19 23.23 16.57 6.32 8.71
#> 187.1 23.1 85 63 158 23.2 117.1 16.1 55.1 69.1 68 188 159.3
#> 9.92 16.92 16.44 22.77 20.14 16.92 17.46 8.71 19.34 23.23 20.62 16.16 10.55
#> 5 41 117.2 125 181 169.1 101 168 76 60.2 69.2 105 158.1
#> 16.43 18.02 17.46 15.65 16.46 22.41 9.97 23.72 19.22 13.15 23.23 19.75 20.14
#> 177.1 158.2 113 18 170 130.1 71 138 71.1 151 163 95 132
#> 12.53 20.14 22.86 15.21 19.54 16.47 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 162 71.2 84 20 3 104 172 82 48 131 152 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.1 131.1 80 118 160 7 9 109 182 147 82.2 82.3 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.1 178 109.1 143 182.1 200 98.2 156 193 112 104.1 31 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.3 147.1 27 138.1 122 193.1 47 156.1 33 120 142 46 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.1 19 67 143.1 67.1 44 44.1 116 165 178.1 80.1 185 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 176 165.1 82.4 72 72.1 17.1 2 152.1 135.1 12 7.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[9]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00882688 0.50229295 0.41250403
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.0510658866 -0.0002831585 -0.1298325856
#> grade_iii, Cure model
#> 1.0026826048
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 139 21.49 1 63 1 0
#> 56 12.21 1 60 0 0
#> 56.1 12.21 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 85 16.44 1 36 0 0
#> 61 10.12 1 36 0 1
#> 89 11.44 1 NA 0 0
#> 107 11.18 1 54 1 0
#> 184 17.77 1 38 0 0
#> 170 19.54 1 43 0 1
#> 52 10.42 1 52 0 1
#> 51 18.23 1 83 0 1
#> 108 18.29 1 39 0 1
#> 150 20.33 1 48 0 0
#> 166 19.98 1 48 0 0
#> 37 12.52 1 57 1 0
#> 96 14.54 1 33 0 1
#> 105 19.75 1 60 0 0
#> 171 16.57 1 41 0 1
#> 181 16.46 1 45 0 1
#> 171.1 16.57 1 41 0 1
#> 101 9.97 1 10 0 1
#> 25 6.32 1 34 1 0
#> 24 23.89 1 38 0 0
#> 107.1 11.18 1 54 1 0
#> 18 15.21 1 49 1 0
#> 76 19.22 1 54 0 1
#> 30 17.43 1 78 0 0
#> 124 9.73 1 NA 1 0
#> 52.1 10.42 1 52 0 1
#> 61.1 10.12 1 36 0 1
#> 86 23.81 1 58 0 1
#> 56.2 12.21 1 60 0 0
#> 39 15.59 1 37 0 1
#> 170.1 19.54 1 43 0 1
#> 50 10.02 1 NA 1 0
#> 16 8.71 1 71 0 1
#> 40 18.00 1 28 1 0
#> 26 15.77 1 49 0 1
#> 16.1 8.71 1 71 0 1
#> 25.1 6.32 1 34 1 0
#> 129 23.41 1 53 1 0
#> 190 20.81 1 42 1 0
#> 14 12.89 1 21 0 0
#> 6 15.64 1 39 0 0
#> 39.1 15.59 1 37 0 1
#> 155 13.08 1 26 0 0
#> 169 22.41 1 46 0 0
#> 5 16.43 1 51 0 1
#> 123 13.00 1 44 1 0
#> 187 9.92 1 39 1 0
#> 168 23.72 1 70 0 0
#> 42 12.43 1 49 0 1
#> 55 19.34 1 69 0 1
#> 52.2 10.42 1 52 0 1
#> 85.1 16.44 1 36 0 0
#> 154 12.63 1 20 1 0
#> 133 14.65 1 57 0 0
#> 117 17.46 1 26 0 1
#> 183 9.24 1 67 1 0
#> 195 11.76 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 123.1 13.00 1 44 1 0
#> 23 16.92 1 61 0 0
#> 171.2 16.57 1 41 0 1
#> 8 18.43 1 32 0 0
#> 150.1 20.33 1 48 0 0
#> 57 14.46 1 45 0 1
#> 125 15.65 1 67 1 0
#> 25.2 6.32 1 34 1 0
#> 96.1 14.54 1 33 0 1
#> 149 8.37 1 33 1 0
#> 100 16.07 1 60 0 0
#> 78 23.88 1 43 0 0
#> 149.1 8.37 1 33 1 0
#> 29 15.45 1 68 1 0
#> 40.1 18.00 1 28 1 0
#> 8.1 18.43 1 32 0 0
#> 59 10.16 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 56.3 12.21 1 60 0 0
#> 188 16.16 1 46 0 1
#> 45 17.42 1 54 0 1
#> 189.1 10.51 1 NA 1 0
#> 86.1 23.81 1 58 0 1
#> 58.1 19.34 1 39 0 0
#> 57.1 14.46 1 45 0 1
#> 128 20.35 1 35 0 1
#> 129.1 23.41 1 53 1 0
#> 39.2 15.59 1 37 0 1
#> 76.1 19.22 1 54 0 1
#> 52.3 10.42 1 52 0 1
#> 16.2 8.71 1 71 0 1
#> 32 20.90 1 37 1 0
#> 149.2 8.37 1 33 1 0
#> 77 7.27 1 67 0 1
#> 96.2 14.54 1 33 0 1
#> 25.3 6.32 1 34 1 0
#> 157 15.10 1 47 0 0
#> 171.3 16.57 1 41 0 1
#> 92 22.92 1 47 0 1
#> 50.1 10.02 1 NA 1 0
#> 26.1 15.77 1 49 0 1
#> 153 21.33 1 55 1 0
#> 88 18.37 1 47 0 0
#> 139.1 21.49 1 63 1 0
#> 30.1 17.43 1 78 0 0
#> 29.1 15.45 1 68 1 0
#> 42.1 12.43 1 49 0 1
#> 52.4 10.42 1 52 0 1
#> 68 20.62 1 44 0 0
#> 128.1 20.35 1 35 0 1
#> 143 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 161 24.00 0 45 0 0
#> 9 24.00 0 31 1 0
#> 118.1 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 126 24.00 0 48 0 0
#> 21 24.00 0 47 0 0
#> 200 24.00 0 64 0 0
#> 7 24.00 0 37 1 0
#> 120 24.00 0 68 0 1
#> 115 24.00 0 NA 1 0
#> 2 24.00 0 9 0 0
#> 138 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 102 24.00 0 49 0 0
#> 71 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 48 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 47 24.00 0 38 0 1
#> 146 24.00 0 63 1 0
#> 146.1 24.00 0 63 1 0
#> 142 24.00 0 53 0 0
#> 112 24.00 0 61 0 0
#> 64 24.00 0 43 0 0
#> 28 24.00 0 67 1 0
#> 176 24.00 0 43 0 1
#> 109 24.00 0 48 0 0
#> 80 24.00 0 41 0 0
#> 95 24.00 0 68 0 1
#> 34 24.00 0 36 0 0
#> 98.1 24.00 0 34 1 0
#> 115.1 24.00 0 NA 1 0
#> 98.2 24.00 0 34 1 0
#> 95.1 24.00 0 68 0 1
#> 3 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 3.1 24.00 0 31 1 0
#> 148.1 24.00 0 61 1 0
#> 21.1 24.00 0 47 0 0
#> 22 24.00 0 52 1 0
#> 120.1 24.00 0 68 0 1
#> 151 24.00 0 42 0 0
#> 87 24.00 0 27 0 0
#> 151.1 24.00 0 42 0 0
#> 21.2 24.00 0 47 0 0
#> 31 24.00 0 36 0 1
#> 147 24.00 0 76 1 0
#> 7.1 24.00 0 37 1 0
#> 71.1 24.00 0 51 0 0
#> 22.1 24.00 0 52 1 0
#> 178 24.00 0 52 1 0
#> 74 24.00 0 43 0 1
#> 27 24.00 0 63 1 0
#> 67 24.00 0 25 0 0
#> 132 24.00 0 55 0 0
#> 138.1 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 103 24.00 0 56 1 0
#> 122 24.00 0 66 0 0
#> 196 24.00 0 19 0 0
#> 73.1 24.00 0 NA 0 1
#> 35 24.00 0 51 0 0
#> 135.1 24.00 0 58 1 0
#> 120.2 24.00 0 68 0 1
#> 103.1 24.00 0 56 1 0
#> 160 24.00 0 31 1 0
#> 33.1 24.00 0 53 0 0
#> 173 24.00 0 19 0 1
#> 48.1 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 176.1 24.00 0 43 0 1
#> 12 24.00 0 63 0 0
#> 74.1 24.00 0 43 0 1
#> 152.1 24.00 0 36 0 1
#> 137 24.00 0 45 1 0
#> 53 24.00 0 32 0 1
#> 186 24.00 0 45 1 0
#> 11 24.00 0 42 0 1
#> 20 24.00 0 46 1 0
#> 104 24.00 0 50 1 0
#> 165 24.00 0 47 0 0
#> 74.2 24.00 0 43 0 1
#> 19 24.00 0 57 0 1
#> 126.1 24.00 0 48 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0511 NA NA NA
#> 2 age, Cure model -0.000283 NA NA NA
#> 3 grade_ii, Cure model -0.130 NA NA NA
#> 4 grade_iii, Cure model 1.00 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00883 NA NA NA
#> 2 grade_ii, Survival model 0.502 NA NA NA
#> 3 grade_iii, Survival model 0.413 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.0510659 -0.0002832 -0.1298326 1.0026826
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.5
#> Residual Deviance: 247.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.0510658866 -0.0002831585 -0.1298325856 1.0026826048
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00882688 0.50229295 0.41250403
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.078380018 0.723041716 0.723041716 0.418873031 0.835722077 0.763993306
#> [7] 0.311693886 0.181172346 0.784736494 0.282969246 0.273256607 0.145820740
#> [13] 0.162990678 0.692531602 0.590777580 0.171982701 0.370547155 0.408924884
#> [19] 0.370547155 0.856451033 0.959583988 0.001853500 0.763993306 0.559957972
#> [25] 0.226108391 0.331021828 0.784736494 0.835722077 0.015337468 0.723041716
#> [31] 0.509710776 0.181172346 0.887557697 0.292774103 0.469121045 0.887557697
#> [37] 0.959583988 0.037342037 0.112212327 0.672041314 0.499455664 0.509710776
#> [43] 0.641411346 0.060978060 0.438787639 0.651701099 0.866830598 0.028599185
#> [49] 0.702747259 0.199027857 0.784736494 0.418873031 0.682316075 0.580435331
#> [55] 0.321387022 0.877188928 0.069696498 0.651701099 0.360500568 0.370547155
#> [61] 0.244637752 0.145820740 0.621063317 0.489261519 0.959583988 0.590777580
#> [67] 0.918508837 0.458949153 0.007505271 0.918508837 0.539702693 0.292774103
#> [73] 0.244637752 0.199027857 0.723041716 0.448869126 0.350569223 0.015337468
#> [79] 0.199027857 0.621063317 0.129323121 0.037342037 0.509710776 0.226108391
#> [85] 0.784736494 0.887557697 0.103664375 0.918508837 0.949217007 0.590777580
#> [91] 0.959583988 0.570165434 0.370547155 0.052657897 0.469121045 0.094979359
#> [97] 0.263519559 0.078380018 0.331021828 0.539702693 0.702747259 0.784736494
#> [103] 0.120670039 0.129323121 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 139 56 56.1 85 61 107 184 170 52 51 108 150 166
#> 21.49 12.21 12.21 16.44 10.12 11.18 17.77 19.54 10.42 18.23 18.29 20.33 19.98
#> 37 96 105 171 181 171.1 101 25 24 107.1 18 76 30
#> 12.52 14.54 19.75 16.57 16.46 16.57 9.97 6.32 23.89 11.18 15.21 19.22 17.43
#> 52.1 61.1 86 56.2 39 170.1 16 40 26 16.1 25.1 129 190
#> 10.42 10.12 23.81 12.21 15.59 19.54 8.71 18.00 15.77 8.71 6.32 23.41 20.81
#> 14 6 39.1 155 169 5 123 187 168 42 55 52.2 85.1
#> 12.89 15.64 15.59 13.08 22.41 16.43 13.00 9.92 23.72 12.43 19.34 10.42 16.44
#> 154 133 117 183 136 123.1 23 171.2 8 150.1 57 125 25.2
#> 12.63 14.65 17.46 9.24 21.83 13.00 16.92 16.57 18.43 20.33 14.46 15.65 6.32
#> 96.1 149 100 78 149.1 29 40.1 8.1 58 56.3 188 45 86.1
#> 14.54 8.37 16.07 23.88 8.37 15.45 18.00 18.43 19.34 12.21 16.16 17.42 23.81
#> 58.1 57.1 128 129.1 39.2 76.1 52.3 16.2 32 149.2 77 96.2 25.3
#> 19.34 14.46 20.35 23.41 15.59 19.22 10.42 8.71 20.90 8.37 7.27 14.54 6.32
#> 157 171.3 92 26.1 153 88 139.1 30.1 29.1 42.1 52.4 68 128.1
#> 15.10 16.57 22.92 15.77 21.33 18.37 21.49 17.43 15.45 12.43 10.42 20.62 20.35
#> 143 118 148 161 9 118.1 126 21 200 7 120 2 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 102 71 135 48 98 47 146 146.1 142 112 64 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 109 80 95 34 98.1 98.2 95.1 3 152 3.1 148.1 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 120.1 151 87 151.1 21.2 31 147 7.1 71.1 22.1 178 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 67 132 138.1 131 103 122 196 35 135.1 120.2 103.1 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 173 48.1 162 54 176.1 12 74.1 152.1 137 53 186 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 104 165 74.2 19 126.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[10]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.00489285 0.05289544 -0.22040253
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.06335249 0.01999215 0.05160241
#> grade_iii, Cure model
#> 0.76017623
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 123 13.00 1 44 1 0
#> 92 22.92 1 47 0 1
#> 133 14.65 1 57 0 0
#> 69 23.23 1 25 0 1
#> 8 18.43 1 32 0 0
#> 26 15.77 1 49 0 1
#> 59 10.16 1 NA 1 0
#> 92.1 22.92 1 47 0 1
#> 13 14.34 1 54 0 1
#> 114 13.68 1 NA 0 0
#> 68 20.62 1 44 0 0
#> 130 16.47 1 53 0 1
#> 90 20.94 1 50 0 1
#> 41 18.02 1 40 1 0
#> 8.1 18.43 1 32 0 0
#> 125 15.65 1 67 1 0
#> 136 21.83 1 43 0 1
#> 70 7.38 1 30 1 0
#> 125.1 15.65 1 67 1 0
#> 93 10.33 1 52 0 1
#> 40 18.00 1 28 1 0
#> 93.1 10.33 1 52 0 1
#> 15 22.68 1 48 0 0
#> 23 16.92 1 61 0 0
#> 139 21.49 1 63 1 0
#> 188 16.16 1 46 0 1
#> 129 23.41 1 53 1 0
#> 189 10.51 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 145 10.07 1 65 1 0
#> 133.1 14.65 1 57 0 0
#> 78 23.88 1 43 0 0
#> 136.1 21.83 1 43 0 1
#> 184 17.77 1 38 0 0
#> 100 16.07 1 60 0 0
#> 107 11.18 1 54 1 0
#> 99 21.19 1 38 0 1
#> 55 19.34 1 69 0 1
#> 171 16.57 1 41 0 1
#> 105 19.75 1 60 0 0
#> 133.2 14.65 1 57 0 0
#> 157 15.10 1 47 0 0
#> 37 12.52 1 57 1 0
#> 99.1 21.19 1 38 0 1
#> 124 9.73 1 NA 1 0
#> 90.1 20.94 1 50 0 1
#> 123.1 13.00 1 44 1 0
#> 14 12.89 1 21 0 0
#> 30 17.43 1 78 0 0
#> 111 17.45 1 47 0 1
#> 36 21.19 1 48 0 1
#> 106 16.67 1 49 1 0
#> 106.1 16.67 1 49 1 0
#> 106.2 16.67 1 49 1 0
#> 56 12.21 1 60 0 0
#> 108 18.29 1 39 0 1
#> 30.1 17.43 1 78 0 0
#> 60 13.15 1 38 1 0
#> 37.1 12.52 1 57 1 0
#> 85 16.44 1 36 0 0
#> 158 20.14 1 74 1 0
#> 99.2 21.19 1 38 0 1
#> 45 17.42 1 54 0 1
#> 45.1 17.42 1 54 0 1
#> 26.1 15.77 1 49 0 1
#> 166 19.98 1 48 0 0
#> 157.1 15.10 1 47 0 0
#> 50 10.02 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 13.1 14.34 1 54 0 1
#> 194 22.40 1 38 0 1
#> 155 13.08 1 26 0 0
#> 184.1 17.77 1 38 0 0
#> 199 19.81 1 NA 0 1
#> 124.1 9.73 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 36.1 21.19 1 48 0 1
#> 181 16.46 1 45 0 1
#> 150 20.33 1 48 0 0
#> 190 20.81 1 42 1 0
#> 180 14.82 1 37 0 0
#> 16 8.71 1 71 0 1
#> 183 9.24 1 67 1 0
#> 129.1 23.41 1 53 1 0
#> 129.2 23.41 1 53 1 0
#> 164 23.60 1 76 0 1
#> 154 12.63 1 20 1 0
#> 13.2 14.34 1 54 0 1
#> 134 17.81 1 47 1 0
#> 189.1 10.51 1 NA 1 0
#> 106.3 16.67 1 49 1 0
#> 145.1 10.07 1 65 1 0
#> 40.1 18.00 1 28 1 0
#> 26.2 15.77 1 49 0 1
#> 140.1 12.68 1 59 1 0
#> 77 7.27 1 67 0 1
#> 51 18.23 1 83 0 1
#> 153.1 21.33 1 55 1 0
#> 113 22.86 1 34 0 0
#> 36.2 21.19 1 48 0 1
#> 110 17.56 1 65 0 1
#> 190.1 20.81 1 42 1 0
#> 51.1 18.23 1 83 0 1
#> 50.1 10.02 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 195 11.76 1 NA 1 0
#> 50.2 10.02 1 NA 1 0
#> 136.2 21.83 1 43 0 1
#> 6 15.64 1 39 0 0
#> 52 10.42 1 52 0 1
#> 117.1 17.46 1 26 0 1
#> 124.2 9.73 1 NA 1 0
#> 83 24.00 0 6 0 0
#> 132 24.00 0 55 0 0
#> 54 24.00 0 53 1 0
#> 121 24.00 0 57 1 0
#> 173 24.00 0 19 0 1
#> 54.1 24.00 0 53 1 0
#> 152 24.00 0 36 0 1
#> 95 24.00 0 68 0 1
#> 178 24.00 0 52 1 0
#> 48 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 95.1 24.00 0 68 0 1
#> 103 24.00 0 56 1 0
#> 104 24.00 0 50 1 0
#> 71 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 83.1 24.00 0 6 0 0
#> 132.1 24.00 0 55 0 0
#> 1 24.00 0 23 1 0
#> 147 24.00 0 76 1 0
#> 173.1 24.00 0 19 0 1
#> 11 24.00 0 42 0 1
#> 48.1 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 131 24.00 0 66 0 0
#> 176 24.00 0 43 0 1
#> 31 24.00 0 36 0 1
#> 151 24.00 0 42 0 0
#> 146 24.00 0 63 1 0
#> 146.1 24.00 0 63 1 0
#> 147.1 24.00 0 76 1 0
#> 48.2 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 141.1 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 131.1 24.00 0 66 0 0
#> 17 24.00 0 38 0 1
#> 95.2 24.00 0 68 0 1
#> 161 24.00 0 45 0 0
#> 198 24.00 0 66 0 1
#> 131.2 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 115 24.00 0 NA 1 0
#> 137 24.00 0 45 1 0
#> 176.1 24.00 0 43 0 1
#> 17.1 24.00 0 38 0 1
#> 82 24.00 0 34 0 0
#> 144 24.00 0 28 0 1
#> 31.1 24.00 0 36 0 1
#> 126 24.00 0 48 0 0
#> 2.1 24.00 0 9 0 0
#> 115.1 24.00 0 NA 1 0
#> 135 24.00 0 58 1 0
#> 102 24.00 0 49 0 0
#> 196 24.00 0 19 0 0
#> 102.1 24.00 0 49 0 0
#> 12 24.00 0 63 0 0
#> 165 24.00 0 47 0 0
#> 83.2 24.00 0 6 0 0
#> 54.2 24.00 0 53 1 0
#> 44 24.00 0 56 0 0
#> 122 24.00 0 66 0 0
#> 131.3 24.00 0 66 0 0
#> 186 24.00 0 45 1 0
#> 7 24.00 0 37 1 0
#> 47 24.00 0 38 0 1
#> 74 24.00 0 43 0 1
#> 186.1 24.00 0 45 1 0
#> 83.3 24.00 0 6 0 0
#> 160 24.00 0 31 1 0
#> 137.1 24.00 0 45 1 0
#> 173.2 24.00 0 19 0 1
#> 47.1 24.00 0 38 0 1
#> 104.1 24.00 0 50 1 0
#> 146.2 24.00 0 63 1 0
#> 12.1 24.00 0 63 0 0
#> 46 24.00 0 71 0 0
#> 12.2 24.00 0 63 0 0
#> 102.2 24.00 0 49 0 0
#> 137.2 24.00 0 45 1 0
#> 11.1 24.00 0 42 0 1
#> 102.3 24.00 0 49 0 0
#> 53 24.00 0 32 0 1
#> 9 24.00 0 31 1 0
#> 74.1 24.00 0 43 0 1
#> 141.2 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.06 NA NA NA
#> 2 age, Cure model 0.0200 NA NA NA
#> 3 grade_ii, Cure model 0.0516 NA NA NA
#> 4 grade_iii, Cure model 0.760 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00489 NA NA NA
#> 2 grade_ii, Survival model 0.0529 NA NA NA
#> 3 grade_iii, Survival model -0.220 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.06335 0.01999 0.05160 0.76018
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 247.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.06335249 0.01999215 0.05160241 0.76017623
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.00489285 0.05289544 -0.22040253
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.83015609 0.10166838 0.76025637 0.08882314 0.39457644 0.67947479
#> [7] 0.10166838 0.78644572 0.33242348 0.63346727 0.28990569 0.44426058
#> [13] 0.39457644 0.70655576 0.16246177 0.98332476 0.70655576 0.92454810
#> [19] 0.45417005 0.92454810 0.13814066 0.57869262 0.19642068 0.66111827
#> [25] 0.05597462 0.85620472 0.94144602 0.76025637 0.01640463 0.16246177
#> [31] 0.48334701 0.67031797 0.90755875 0.23004305 0.38441534 0.62423660
#> [37] 0.37422074 0.76025637 0.73352454 0.88200731 0.23004305 0.28990569
#> [43] 0.83015609 0.84749842 0.54099054 0.53131611 0.23004305 0.58813508
#> [49] 0.58813508 0.58813508 0.89903293 0.41446584 0.54099054 0.81259617
#> [55] 0.88200731 0.65191797 0.35356272 0.23004305 0.55985576 0.55985576
#> [61] 0.67947479 0.36393052 0.73352454 0.20815107 0.78644572 0.15028428
#> [67] 0.82138249 0.48334701 0.51214010 0.23004305 0.64269260 0.34303619
#> [73] 0.31137818 0.75132428 0.96659308 0.95820883 0.05597462 0.05597462
#> [79] 0.03688592 0.87338724 0.78644572 0.47359758 0.58813508 0.94144602
#> [85] 0.45417005 0.67947479 0.85620472 0.99166636 0.42453994 0.20815107
#> [91] 0.12570864 0.23004305 0.50249310 0.31137818 0.42453994 0.97496750
#> [97] 0.16246177 0.72451314 0.91605479 0.51214010 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 123 92 133 69 8 26 92.1 13 68 130 90 41 8.1
#> 13.00 22.92 14.65 23.23 18.43 15.77 22.92 14.34 20.62 16.47 20.94 18.02 18.43
#> 125 136 70 125.1 93 40 93.1 15 23 139 188 129 140
#> 15.65 21.83 7.38 15.65 10.33 18.00 10.33 22.68 16.92 21.49 16.16 23.41 12.68
#> 145 133.1 78 136.1 184 100 107 99 55 171 105 133.2 157
#> 10.07 14.65 23.88 21.83 17.77 16.07 11.18 21.19 19.34 16.57 19.75 14.65 15.10
#> 37 99.1 90.1 123.1 14 30 111 36 106 106.1 106.2 56 108
#> 12.52 21.19 20.94 13.00 12.89 17.43 17.45 21.19 16.67 16.67 16.67 12.21 18.29
#> 30.1 60 37.1 85 158 99.2 45 45.1 26.1 166 157.1 153 13.1
#> 17.43 13.15 12.52 16.44 20.14 21.19 17.42 17.42 15.77 19.98 15.10 21.33 14.34
#> 194 155 184.1 117 36.1 181 150 190 180 16 183 129.1 129.2
#> 22.40 13.08 17.77 17.46 21.19 16.46 20.33 20.81 14.82 8.71 9.24 23.41 23.41
#> 164 154 13.2 134 106.3 145.1 40.1 26.2 140.1 77 51 153.1 113
#> 23.60 12.63 14.34 17.81 16.67 10.07 18.00 15.77 12.68 7.27 18.23 21.33 22.86
#> 36.2 110 190.1 51.1 149 136.2 6 52 117.1 83 132 54 121
#> 21.19 17.56 20.81 18.23 8.37 21.83 15.64 10.42 17.46 24.00 24.00 24.00 24.00
#> 173 54.1 152 95 178 48 185 95.1 103 104 71 2 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 1 147 173.1 11 48.1 75 131 176 31 151 146 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147.1 48.2 141 141.1 35 27 131.1 17 95.2 161 198 131.2 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 176.1 17.1 82 144 31.1 126 2.1 135 102 196 102.1 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 83.2 54.2 44 122 131.3 186 7 47 74 186.1 83.3 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 173.2 47.1 104.1 146.2 12.1 46 12.2 102.2 137.2 11.1 102.3 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 74.1 141.2 148
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[11]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006617498 0.839206751 0.748192226
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.99631598 0.01590126 0.32347433
#> grade_iii, Cure model
#> 0.84705110
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 159 10.55 1 50 0 1
#> 149 8.37 1 33 1 0
#> 70 7.38 1 30 1 0
#> 110 17.56 1 65 0 1
#> 41 18.02 1 40 1 0
#> 125 15.65 1 67 1 0
#> 32 20.90 1 37 1 0
#> 179 18.63 1 42 0 0
#> 197 21.60 1 69 1 0
#> 99 21.19 1 38 0 1
#> 32.1 20.90 1 37 1 0
#> 117 17.46 1 26 0 1
#> 25 6.32 1 34 1 0
#> 93 10.33 1 52 0 1
#> 105 19.75 1 60 0 0
#> 130 16.47 1 53 0 1
#> 184 17.77 1 38 0 0
#> 32.2 20.90 1 37 1 0
#> 110.1 17.56 1 65 0 1
#> 43 12.10 1 61 0 1
#> 37 12.52 1 57 1 0
#> 60 13.15 1 38 1 0
#> 97 19.14 1 65 0 1
#> 43.1 12.10 1 61 0 1
#> 190 20.81 1 42 1 0
#> 92 22.92 1 47 0 1
#> 52 10.42 1 52 0 1
#> 30 17.43 1 78 0 0
#> 4 17.64 1 NA 0 1
#> 78 23.88 1 43 0 0
#> 159.1 10.55 1 50 0 1
#> 52.1 10.42 1 52 0 1
#> 81 14.06 1 34 0 0
#> 90 20.94 1 50 0 1
#> 4.1 17.64 1 NA 0 1
#> 113 22.86 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 32.3 20.90 1 37 1 0
#> 79 16.23 1 54 1 0
#> 189 10.51 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 56 12.21 1 60 0 0
#> 5 16.43 1 51 0 1
#> 150 20.33 1 48 0 0
#> 157 15.10 1 47 0 0
#> 57 14.46 1 45 0 1
#> 93.1 10.33 1 52 0 1
#> 52.2 10.42 1 52 0 1
#> 189.1 10.51 1 NA 1 0
#> 157.1 15.10 1 47 0 0
#> 195.1 11.76 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 25.1 6.32 1 34 1 0
#> 59 10.16 1 NA 1 0
#> 93.2 10.33 1 52 0 1
#> 167 15.55 1 56 1 0
#> 184.1 17.77 1 38 0 0
#> 30.1 17.43 1 78 0 0
#> 124 9.73 1 NA 1 0
#> 37.1 12.52 1 57 1 0
#> 57.1 14.46 1 45 0 1
#> 93.3 10.33 1 52 0 1
#> 154 12.63 1 20 1 0
#> 49 12.19 1 48 1 0
#> 56.1 12.21 1 60 0 0
#> 45 17.42 1 54 0 1
#> 114 13.68 1 NA 0 0
#> 153 21.33 1 55 1 0
#> 168 23.72 1 70 0 0
#> 10 10.53 1 34 0 0
#> 6 15.64 1 39 0 0
#> 55 19.34 1 69 0 1
#> 177 12.53 1 75 0 0
#> 93.4 10.33 1 52 0 1
#> 188 16.16 1 46 0 1
#> 4.2 17.64 1 NA 0 1
#> 149.1 8.37 1 33 1 0
#> 57.2 14.46 1 45 0 1
#> 134 17.81 1 47 1 0
#> 24.1 23.89 1 38 0 0
#> 41.1 18.02 1 40 1 0
#> 89 11.44 1 NA 0 0
#> 168.1 23.72 1 70 0 0
#> 189.2 10.51 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 158 20.14 1 74 1 0
#> 113.1 22.86 1 34 0 0
#> 189.3 10.51 1 NA 1 0
#> 150.1 20.33 1 48 0 0
#> 192 16.44 1 31 1 0
#> 187 9.92 1 39 1 0
#> 51 18.23 1 83 0 1
#> 145 10.07 1 65 1 0
#> 184.2 17.77 1 38 0 0
#> 43.2 12.10 1 61 0 1
#> 128 20.35 1 35 0 1
#> 192.1 16.44 1 31 1 0
#> 61 10.12 1 36 0 1
#> 125.1 15.65 1 67 1 0
#> 175 21.91 1 43 0 0
#> 16 8.71 1 71 0 1
#> 15 22.68 1 48 0 0
#> 58 19.34 1 39 0 0
#> 179.1 18.63 1 42 0 0
#> 57.3 14.46 1 45 0 1
#> 58.1 19.34 1 39 0 0
#> 59.1 10.16 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 92.1 22.92 1 47 0 1
#> 36 21.19 1 48 0 1
#> 88 18.37 1 47 0 0
#> 145.1 10.07 1 65 1 0
#> 3 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 64 24.00 0 43 0 0
#> 151 24.00 0 42 0 0
#> 95 24.00 0 68 0 1
#> 62 24.00 0 71 0 0
#> 102 24.00 0 49 0 0
#> 84 24.00 0 39 0 1
#> 160 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 2.1 24.00 0 9 0 0
#> 176 24.00 0 43 0 1
#> 141 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 173 24.00 0 19 0 1
#> 109 24.00 0 48 0 0
#> 34 24.00 0 36 0 0
#> 104 24.00 0 50 1 0
#> 137 24.00 0 45 1 0
#> 186 24.00 0 45 1 0
#> 62.1 24.00 0 71 0 0
#> 151.1 24.00 0 42 0 0
#> 198 24.00 0 66 0 1
#> 102.1 24.00 0 49 0 0
#> 161 24.00 0 45 0 0
#> 87 24.00 0 27 0 0
#> 44 24.00 0 56 0 0
#> 163 24.00 0 66 0 0
#> 104.1 24.00 0 50 1 0
#> 35 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 62.2 24.00 0 71 0 0
#> 72 24.00 0 40 0 1
#> 28 24.00 0 67 1 0
#> 200 24.00 0 64 0 0
#> 109.1 24.00 0 48 0 0
#> 160.1 24.00 0 31 1 0
#> 72.1 24.00 0 40 0 1
#> 151.2 24.00 0 42 0 0
#> 152.1 24.00 0 36 0 1
#> 82 24.00 0 34 0 0
#> 109.2 24.00 0 48 0 0
#> 116 24.00 0 58 0 1
#> 198.1 24.00 0 66 0 1
#> 2.2 24.00 0 9 0 0
#> 21 24.00 0 47 0 0
#> 160.2 24.00 0 31 1 0
#> 141.1 24.00 0 44 1 0
#> 173.1 24.00 0 19 0 1
#> 1 24.00 0 23 1 0
#> 147 24.00 0 76 1 0
#> 196 24.00 0 19 0 0
#> 147.1 24.00 0 76 1 0
#> 2.3 24.00 0 9 0 0
#> 94 24.00 0 51 0 1
#> 104.2 24.00 0 50 1 0
#> 82.1 24.00 0 34 0 0
#> 74 24.00 0 43 0 1
#> 87.1 24.00 0 27 0 0
#> 102.2 24.00 0 49 0 0
#> 7 24.00 0 37 1 0
#> 12 24.00 0 63 0 0
#> 176.1 24.00 0 43 0 1
#> 62.3 24.00 0 71 0 0
#> 193 24.00 0 45 0 1
#> 146 24.00 0 63 1 0
#> 109.3 24.00 0 48 0 0
#> 34.1 24.00 0 36 0 0
#> 152.2 24.00 0 36 0 1
#> 160.3 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 147.2 24.00 0 76 1 0
#> 165 24.00 0 47 0 0
#> 176.2 24.00 0 43 0 1
#> 74.1 24.00 0 43 0 1
#> 98 24.00 0 34 1 0
#> 48 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 2.4 24.00 0 9 0 0
#> 185 24.00 0 44 1 0
#> 44.1 24.00 0 56 0 0
#> 148 24.00 0 61 1 0
#> 146.1 24.00 0 63 1 0
#> 147.3 24.00 0 76 1 0
#> 12.1 24.00 0 63 0 0
#> 172 24.00 0 41 0 0
#> 160.4 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.996 NA NA NA
#> 2 age, Cure model 0.0159 NA NA NA
#> 3 grade_ii, Cure model 0.323 NA NA NA
#> 4 grade_iii, Cure model 0.847 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00662 NA NA NA
#> 2 grade_ii, Survival model 0.839 NA NA NA
#> 3 grade_iii, Survival model 0.748 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.9963 0.0159 0.3235 0.8471
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 257.3
#> Residual Deviance: 249 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.99631598 0.01590126 0.32347433 0.84705110
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006617498 0.839206751 0.748192226
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9090658 0.9797644 0.9879416 0.6990912 0.6532394 0.7863945 0.4830278
#> [8] 0.6193178 0.4092834 0.4423252 0.4830278 0.7134990 0.9920080 0.9369235
#> [15] 0.5747231 0.7481701 0.6765522 0.4830278 0.6990912 0.8946525 0.8693750
#> [22] 0.8535512 0.6106354 0.8946525 0.5250758 0.2904029 0.9232320 0.7276312
#> [29] 0.1526196 0.9090658 0.9232320 0.8481679 0.4698297 0.3308415 0.4830278
#> [36] 0.7740278 0.0701256 0.8795393 0.7676808 0.5455535 0.8155108 0.8268046
#> [43] 0.9369235 0.9232320 0.8155108 0.8098153 0.9920080 0.9369235 0.8040303
#> [50] 0.6765522 0.7276312 0.8693750 0.8268046 0.9369235 0.8588684 0.8896466
#> [57] 0.8795393 0.7413875 0.4265483 0.1972150 0.9185059 0.7981457 0.5841208
#> [64] 0.8641320 0.9369235 0.7802568 0.9797644 0.8268046 0.6688803 0.0701256
#> [71] 0.6532394 0.1972150 0.7206303 0.5652499 0.3308415 0.5455535 0.7548319
#> [78] 0.9713964 0.6449700 0.9629309 0.6765522 0.8946525 0.5354775 0.7548319
#> [85] 0.9585910 0.7863945 0.3898424 0.9756017 0.3700773 0.5841208 0.6193178
#> [92] 0.8268046 0.5841208 0.2615971 0.2904029 0.4423252 0.6364087 0.9629309
#> [99] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 159 149 70 110 41 125 32 179 197 99 32.1 117 25
#> 10.55 8.37 7.38 17.56 18.02 15.65 20.90 18.63 21.60 21.19 20.90 17.46 6.32
#> 93 105 130 184 32.2 110.1 43 37 60 97 43.1 190 92
#> 10.33 19.75 16.47 17.77 20.90 17.56 12.10 12.52 13.15 19.14 12.10 20.81 22.92
#> 52 30 78 159.1 52.1 81 90 113 32.3 79 24 56 5
#> 10.42 17.43 23.88 10.55 10.42 14.06 20.94 22.86 20.90 16.23 23.89 12.21 16.43
#> 150 157 57 93.1 52.2 157.1 18 25.1 93.2 167 184.1 30.1 37.1
#> 20.33 15.10 14.46 10.33 10.42 15.10 15.21 6.32 10.33 15.55 17.77 17.43 12.52
#> 57.1 93.3 154 49 56.1 45 153 168 10 6 55 177 93.4
#> 14.46 10.33 12.63 12.19 12.21 17.42 21.33 23.72 10.53 15.64 19.34 12.53 10.33
#> 188 149.1 57.2 134 24.1 41.1 168.1 111 158 113.1 150.1 192 187
#> 16.16 8.37 14.46 17.81 23.89 18.02 23.72 17.45 20.14 22.86 20.33 16.44 9.92
#> 51 145 184.2 43.2 128 192.1 61 125.1 175 16 15 58 179.1
#> 18.23 10.07 17.77 12.10 20.35 16.44 10.12 15.65 21.91 8.71 22.68 19.34 18.63
#> 57.3 58.1 69 92.1 36 88 145.1 3 22 64 151 95 62
#> 14.46 19.34 23.23 22.92 21.19 18.37 10.07 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 84 160 2 2.1 176 141 38 122 173 109 34 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 186 62.1 151.1 198 102.1 161 87 44 163 104.1 35 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.2 72 28 200 109.1 160.1 72.1 151.2 152.1 82 109.2 116 198.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.2 21 160.2 141.1 173.1 1 147 196 147.1 2.3 94 104.2 82.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 87.1 102.2 7 12 176.1 62.3 193 146 109.3 34.1 152.2 160.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 147.2 165 176.2 74.1 98 48 174 2.4 185 44.1 148 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147.3 12.1 172 160.4
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[12]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0002362012 0.5683385412 0.4105592752
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.36437328 0.01206649 -0.40704511
#> grade_iii, Cure model
#> 0.38657217
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 153 21.33 1 55 1 0
#> 187 9.92 1 39 1 0
#> 139 21.49 1 63 1 0
#> 93 10.33 1 52 0 1
#> 32 20.90 1 37 1 0
#> 105 19.75 1 60 0 0
#> 58 19.34 1 39 0 0
#> 129 23.41 1 53 1 0
#> 194 22.40 1 38 0 1
#> 96 14.54 1 33 0 1
#> 40 18.00 1 28 1 0
#> 169 22.41 1 46 0 0
#> 100 16.07 1 60 0 0
#> 105.1 19.75 1 60 0 0
#> 90 20.94 1 50 0 1
#> 49 12.19 1 48 1 0
#> 197 21.60 1 69 1 0
#> 124 9.73 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 194.1 22.40 1 38 0 1
#> 184 17.77 1 38 0 0
#> 5 16.43 1 51 0 1
#> 63 22.77 1 31 1 0
#> 166 19.98 1 48 0 0
#> 61 10.12 1 36 0 1
#> 169.1 22.41 1 46 0 0
#> 107 11.18 1 54 1 0
#> 85 16.44 1 36 0 0
#> 91 5.33 1 61 0 1
#> 105.2 19.75 1 60 0 0
#> 88 18.37 1 47 0 0
#> 39 15.59 1 37 0 1
#> 57 14.46 1 45 0 1
#> 14 12.89 1 21 0 0
#> 56 12.21 1 60 0 0
#> 92 22.92 1 47 0 1
#> 101 9.97 1 10 0 1
#> 42 12.43 1 49 0 1
#> 96.1 14.54 1 33 0 1
#> 29 15.45 1 68 1 0
#> 140 12.68 1 59 1 0
#> 99 21.19 1 38 0 1
#> 10 10.53 1 34 0 0
#> 51 18.23 1 83 0 1
#> 39.1 15.59 1 37 0 1
#> 76 19.22 1 54 0 1
#> 139.1 21.49 1 63 1 0
#> 4 17.64 1 NA 0 1
#> 85.1 16.44 1 36 0 0
#> 114 13.68 1 NA 0 0
#> 90.1 20.94 1 50 0 1
#> 61.1 10.12 1 36 0 1
#> 108 18.29 1 39 0 1
#> 166.1 19.98 1 48 0 0
#> 155 13.08 1 26 0 0
#> 127 3.53 1 62 0 1
#> 50 10.02 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 158 20.14 1 74 1 0
#> 110.1 17.56 1 65 0 1
#> 39.2 15.59 1 37 0 1
#> 184.1 17.77 1 38 0 0
#> 171 16.57 1 41 0 1
#> 59 10.16 1 NA 1 0
#> 59.1 10.16 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 149 8.37 1 33 1 0
#> 184.2 17.77 1 38 0 0
#> 40.1 18.00 1 28 1 0
#> 125 15.65 1 67 1 0
#> 169.2 22.41 1 46 0 0
#> 107.1 11.18 1 54 1 0
#> 56.1 12.21 1 60 0 0
#> 124.1 9.73 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 85.2 16.44 1 36 0 0
#> 110.2 17.56 1 65 0 1
#> 5.1 16.43 1 51 0 1
#> 124.2 9.73 1 NA 1 0
#> 157 15.10 1 47 0 0
#> 18 15.21 1 49 1 0
#> 113 22.86 1 34 0 0
#> 183 9.24 1 67 1 0
#> 56.2 12.21 1 60 0 0
#> 70 7.38 1 30 1 0
#> 40.2 18.00 1 28 1 0
#> 177 12.53 1 75 0 0
#> 183.1 9.24 1 67 1 0
#> 187.1 9.92 1 39 1 0
#> 24 23.89 1 38 0 0
#> 100.1 16.07 1 60 0 0
#> 69 23.23 1 25 0 1
#> 41 18.02 1 40 1 0
#> 189 10.51 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 140.1 12.68 1 59 1 0
#> 105.3 19.75 1 60 0 0
#> 170 19.54 1 43 0 1
#> 29.1 15.45 1 68 1 0
#> 86 23.81 1 58 0 1
#> 23 16.92 1 61 0 0
#> 150.1 20.33 1 48 0 0
#> 168 23.72 1 70 0 0
#> 93.1 10.33 1 52 0 1
#> 157.1 15.10 1 47 0 0
#> 18.1 15.21 1 49 1 0
#> 49.1 12.19 1 48 1 0
#> 199 19.81 1 NA 0 1
#> 149.1 8.37 1 33 1 0
#> 114.1 13.68 1 NA 0 0
#> 78 23.88 1 43 0 0
#> 78.1 23.88 1 43 0 0
#> 138 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 33 24.00 0 53 0 0
#> 95 24.00 0 68 0 1
#> 21 24.00 0 47 0 0
#> 48 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 174 24.00 0 49 1 0
#> 142 24.00 0 53 0 0
#> 135 24.00 0 58 1 0
#> 72 24.00 0 40 0 1
#> 122 24.00 0 66 0 0
#> 35 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 182 24.00 0 35 0 0
#> 116 24.00 0 58 0 1
#> 54 24.00 0 53 1 0
#> 7 24.00 0 37 1 0
#> 80 24.00 0 41 0 0
#> 103 24.00 0 56 1 0
#> 82 24.00 0 34 0 0
#> 80.1 24.00 0 41 0 0
#> 83 24.00 0 6 0 0
#> 54.1 24.00 0 53 1 0
#> 7.1 24.00 0 37 1 0
#> 53 24.00 0 32 0 1
#> 27 24.00 0 63 1 0
#> 162 24.00 0 51 0 0
#> 135.1 24.00 0 58 1 0
#> 65 24.00 0 57 1 0
#> 118 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 34.1 24.00 0 36 0 0
#> 20 24.00 0 46 1 0
#> 156 24.00 0 50 1 0
#> 163 24.00 0 66 0 0
#> 119 24.00 0 17 0 0
#> 185 24.00 0 44 1 0
#> 54.2 24.00 0 53 1 0
#> 12 24.00 0 63 0 0
#> 27.1 24.00 0 63 1 0
#> 82.1 24.00 0 34 0 0
#> 200 24.00 0 64 0 0
#> 160 24.00 0 31 1 0
#> 7.2 24.00 0 37 1 0
#> 186 24.00 0 45 1 0
#> 2 24.00 0 9 0 0
#> 147 24.00 0 76 1 0
#> 103.1 24.00 0 56 1 0
#> 2.1 24.00 0 9 0 0
#> 185.1 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 17 24.00 0 38 0 1
#> 135.2 24.00 0 58 1 0
#> 94 24.00 0 51 0 1
#> 84 24.00 0 39 0 1
#> 2.2 24.00 0 9 0 0
#> 1 24.00 0 23 1 0
#> 115 24.00 0 NA 1 0
#> 17.1 24.00 0 38 0 1
#> 46 24.00 0 71 0 0
#> 186.1 24.00 0 45 1 0
#> 82.2 24.00 0 34 0 0
#> 3 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 47 24.00 0 38 0 1
#> 112 24.00 0 61 0 0
#> 135.3 24.00 0 58 1 0
#> 121 24.00 0 57 1 0
#> 73 24.00 0 NA 0 1
#> 176 24.00 0 43 0 1
#> 116.1 24.00 0 58 0 1
#> 191 24.00 0 60 0 1
#> 44 24.00 0 56 0 0
#> 54.3 24.00 0 53 1 0
#> 138.1 24.00 0 44 1 0
#> 82.3 24.00 0 34 0 0
#> 27.2 24.00 0 63 1 0
#> 198 24.00 0 66 0 1
#> 19 24.00 0 57 0 1
#> 71 24.00 0 51 0 0
#> 198.1 24.00 0 66 0 1
#> 3.1 24.00 0 31 1 0
#> 142.1 24.00 0 53 0 0
#> 35.1 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 104 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.364 NA NA NA
#> 2 age, Cure model 0.0121 NA NA NA
#> 3 grade_ii, Cure model -0.407 NA NA NA
#> 4 grade_iii, Cure model 0.387 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000236 NA NA NA
#> 2 grade_ii, Survival model 0.568 NA NA NA
#> 3 grade_iii, Survival model 0.411 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.36437 0.01207 -0.40705 0.38657
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 252.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.36437328 0.01206649 -0.40704511 0.38657217
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0002362012 0.5683385412 0.4105592752
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.29372603 0.93658655 0.27082906 0.90003844 0.33722999 0.39854656
#> [7] 0.44771558 0.11642223 0.23280163 0.76225087 0.50653607 0.19349598
#> [13] 0.66445807 0.39854656 0.31616257 0.85515124 0.25826925 0.65593657
#> [19] 0.23280163 0.53346068 0.63883031 0.17936795 0.37843578 0.91473099
#> [25] 0.19349598 0.87023944 0.61298198 0.98609616 0.39854656 0.46762556
#> [31] 0.68981902 0.77795407 0.79365344 0.83230387 0.14925892 0.92930171
#> [37] 0.82461428 0.76225087 0.71434833 0.80150249 0.30505178 0.88512429
#> [43] 0.48731099 0.68981902 0.45772762 0.27082906 0.61298198 0.31616257
#> [49] 0.91473099 0.47752118 0.37843578 0.78580400 0.99306098 0.56037334
#> [55] 0.36823700 0.56037334 0.68981902 0.53346068 0.60423871 0.89259776
#> [61] 0.96509567 0.53346068 0.50653607 0.68138564 0.19349598 0.87023944
#> [67] 0.83230387 0.58661710 0.61298198 0.56037334 0.63883031 0.74637782
#> [73] 0.73050101 0.16431851 0.95092588 0.83230387 0.97910520 0.50653607
#> [79] 0.81688685 0.95092588 0.93658655 0.01498700 0.66445807 0.13336019
#> [85] 0.49699622 0.34767476 0.80150249 0.39854656 0.43770148 0.71434833
#> [91] 0.07813495 0.59542885 0.34767476 0.09730372 0.90003844 0.74637782
#> [97] 0.73050101 0.85515124 0.96509567 0.04037650 0.04037650 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 153 187 139 93 32 105 58 129 194 96 40 169 100
#> 21.33 9.92 21.49 10.33 20.90 19.75 19.34 23.41 22.40 14.54 18.00 22.41 16.07
#> 105.1 90 49 197 79 194.1 184 5 63 166 61 169.1 107
#> 19.75 20.94 12.19 21.60 16.23 22.40 17.77 16.43 22.77 19.98 10.12 22.41 11.18
#> 85 91 105.2 88 39 57 14 56 92 101 42 96.1 29
#> 16.44 5.33 19.75 18.37 15.59 14.46 12.89 12.21 22.92 9.97 12.43 14.54 15.45
#> 140 99 10 51 39.1 76 139.1 85.1 90.1 61.1 108 166.1 155
#> 12.68 21.19 10.53 18.23 15.59 19.22 21.49 16.44 20.94 10.12 18.29 19.98 13.08
#> 127 110 158 110.1 39.2 184.1 171 52 149 184.2 40.1 125 169.2
#> 3.53 17.56 20.14 17.56 15.59 17.77 16.57 10.42 8.37 17.77 18.00 15.65 22.41
#> 107.1 56.1 111 85.2 110.2 5.1 157 18 113 183 56.2 70 40.2
#> 11.18 12.21 17.45 16.44 17.56 16.43 15.10 15.21 22.86 9.24 12.21 7.38 18.00
#> 177 183.1 187.1 24 100.1 69 41 150 140.1 105.3 170 29.1 86
#> 12.53 9.24 9.92 23.89 16.07 23.23 18.02 20.33 12.68 19.75 19.54 15.45 23.81
#> 23 150.1 168 93.1 157.1 18.1 49.1 149.1 78 78.1 138 152 33
#> 16.92 20.33 23.72 10.33 15.10 15.21 12.19 8.37 23.88 23.88 24.00 24.00 24.00
#> 95 21 48 31 174 142 135 72 122 35 9 144 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 54 7 80 103 82 80.1 83 54.1 7.1 53 27 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 65 118 34 34.1 20 156 163 119 185 54.2 12 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.1 200 160 7.2 186 2 147 103.1 2.1 185.1 148 17 135.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 84 2.2 1 17.1 46 186.1 82.2 3 11 47 112 135.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 176 116.1 191 44 54.3 138.1 82.3 27.2 198 19 71 198.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 142.1 35.1 126 104
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[13]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.02161283 1.12994312 0.73182776
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.549799793 0.005822849 0.233742163
#> grade_iii, Cure model
#> 1.199108395
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 123 13.00 1 44 1 0
#> 57 14.46 1 45 0 1
#> 99 21.19 1 38 0 1
#> 24 23.89 1 38 0 0
#> 88 18.37 1 47 0 0
#> 14 12.89 1 21 0 0
#> 159 10.55 1 50 0 1
#> 167 15.55 1 56 1 0
#> 106 16.67 1 49 1 0
#> 10 10.53 1 34 0 0
#> 114 13.68 1 NA 0 0
#> 86 23.81 1 58 0 1
#> 16 8.71 1 71 0 1
#> 188 16.16 1 46 0 1
#> 110 17.56 1 65 0 1
#> 45 17.42 1 54 0 1
#> 183 9.24 1 67 1 0
#> 150 20.33 1 48 0 0
#> 134 17.81 1 47 1 0
#> 181 16.46 1 45 0 1
#> 124 9.73 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 123.1 13.00 1 44 1 0
#> 108 18.29 1 39 0 1
#> 139 21.49 1 63 1 0
#> 101 9.97 1 10 0 1
#> 175 21.91 1 43 0 0
#> 100 16.07 1 60 0 0
#> 60 13.15 1 38 1 0
#> 177 12.53 1 75 0 0
#> 150.1 20.33 1 48 0 0
#> 61 10.12 1 36 0 1
#> 101.1 9.97 1 10 0 1
#> 43 12.10 1 61 0 1
#> 108.1 18.29 1 39 0 1
#> 59 10.16 1 NA 1 0
#> 123.2 13.00 1 44 1 0
#> 60.1 13.15 1 38 1 0
#> 108.2 18.29 1 39 0 1
#> 124.1 9.73 1 NA 1 0
#> 108.3 18.29 1 39 0 1
#> 130 16.47 1 53 0 1
#> 169 22.41 1 46 0 0
#> 194 22.40 1 38 0 1
#> 188.1 16.16 1 46 0 1
#> 155 13.08 1 26 0 0
#> 159.1 10.55 1 50 0 1
#> 124.2 9.73 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 42 12.43 1 49 0 1
#> 195 11.76 1 NA 1 0
#> 99.1 21.19 1 38 0 1
#> 189 10.51 1 NA 1 0
#> 10.1 10.53 1 34 0 0
#> 66 22.13 1 53 0 0
#> 55 19.34 1 69 0 1
#> 85 16.44 1 36 0 0
#> 5 16.43 1 51 0 1
#> 8 18.43 1 32 0 0
#> 51 18.23 1 83 0 1
#> 127 3.53 1 62 0 1
#> 134.1 17.81 1 47 1 0
#> 150.2 20.33 1 48 0 0
#> 117 17.46 1 26 0 1
#> 42.1 12.43 1 49 0 1
#> 197 21.60 1 69 1 0
#> 187 9.92 1 39 1 0
#> 14.1 12.89 1 21 0 0
#> 25 6.32 1 34 1 0
#> 81 14.06 1 34 0 0
#> 37 12.52 1 57 1 0
#> 5.1 16.43 1 51 0 1
#> 168 23.72 1 70 0 0
#> 129 23.41 1 53 1 0
#> 140 12.68 1 59 1 0
#> 130.1 16.47 1 53 0 1
#> 59.1 10.16 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 61.1 10.12 1 36 0 1
#> 168.1 23.72 1 70 0 0
#> 110.1 17.56 1 65 0 1
#> 70 7.38 1 30 1 0
#> 36.1 21.19 1 48 0 1
#> 41 18.02 1 40 1 0
#> 195.1 11.76 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 89 11.44 1 NA 0 0
#> 79 16.23 1 54 1 0
#> 86.1 23.81 1 58 0 1
#> 175.1 21.91 1 43 0 0
#> 16.1 8.71 1 71 0 1
#> 37.1 12.52 1 57 1 0
#> 61.2 10.12 1 36 0 1
#> 15.1 22.68 1 48 0 0
#> 170 19.54 1 43 0 1
#> 134.2 17.81 1 47 1 0
#> 99.2 21.19 1 38 0 1
#> 60.2 13.15 1 38 1 0
#> 180 14.82 1 37 0 0
#> 88.1 18.37 1 47 0 0
#> 49 12.19 1 48 1 0
#> 180.1 14.82 1 37 0 0
#> 194.1 22.40 1 38 0 1
#> 24.1 23.89 1 38 0 0
#> 96 14.54 1 33 0 1
#> 41.1 18.02 1 40 1 0
#> 159.2 10.55 1 50 0 1
#> 117.1 17.46 1 26 0 1
#> 139.1 21.49 1 63 1 0
#> 41.2 18.02 1 40 1 0
#> 24.2 23.89 1 38 0 0
#> 18 15.21 1 49 1 0
#> 178 24.00 0 52 1 0
#> 48 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 73 24.00 0 NA 0 1
#> 27 24.00 0 63 1 0
#> 146 24.00 0 63 1 0
#> 185 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 12 24.00 0 63 0 0
#> 174 24.00 0 49 1 0
#> 2 24.00 0 9 0 0
#> 172 24.00 0 41 0 0
#> 20 24.00 0 46 1 0
#> 152 24.00 0 36 0 1
#> 82 24.00 0 34 0 0
#> 165 24.00 0 47 0 0
#> 47 24.00 0 38 0 1
#> 196 24.00 0 19 0 0
#> 132.1 24.00 0 55 0 0
#> 31 24.00 0 36 0 1
#> 34 24.00 0 36 0 0
#> 54 24.00 0 53 1 0
#> 28 24.00 0 67 1 0
#> 33 24.00 0 53 0 0
#> 2.1 24.00 0 9 0 0
#> 138 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 182 24.00 0 35 0 0
#> 173 24.00 0 19 0 1
#> 73.1 24.00 0 NA 0 1
#> 1.1 24.00 0 23 1 0
#> 83 24.00 0 6 0 0
#> 27.1 24.00 0 63 1 0
#> 47.1 24.00 0 38 0 1
#> 131 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 83.1 24.00 0 6 0 0
#> 163 24.00 0 66 0 0
#> 143 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 116 24.00 0 58 0 1
#> 135 24.00 0 58 1 0
#> 65 24.00 0 57 1 0
#> 132.2 24.00 0 55 0 0
#> 94 24.00 0 51 0 1
#> 176 24.00 0 43 0 1
#> 44 24.00 0 56 0 0
#> 82.1 24.00 0 34 0 0
#> 172.1 24.00 0 41 0 0
#> 71 24.00 0 51 0 0
#> 138.1 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 33.1 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 173.1 24.00 0 19 0 1
#> 172.2 24.00 0 41 0 0
#> 146.1 24.00 0 63 1 0
#> 9 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 186 24.00 0 45 1 0
#> 34.1 24.00 0 36 0 0
#> 44.1 24.00 0 56 0 0
#> 185.1 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 98 24.00 0 34 1 0
#> 33.2 24.00 0 53 0 0
#> 118 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 38.1 24.00 0 31 1 0
#> 71.1 24.00 0 51 0 0
#> 165.1 24.00 0 47 0 0
#> 47.2 24.00 0 38 0 1
#> 191.1 24.00 0 60 0 1
#> 87 24.00 0 27 0 0
#> 71.2 24.00 0 51 0 0
#> 143.1 24.00 0 51 0 0
#> 147.1 24.00 0 76 1 0
#> 87.1 24.00 0 27 0 0
#> 11 24.00 0 42 0 1
#> 161 24.00 0 45 0 0
#> 71.3 24.00 0 51 0 0
#> 20.1 24.00 0 46 1 0
#> 200 24.00 0 64 0 0
#> 144 24.00 0 28 0 1
#> 186.1 24.00 0 45 1 0
#> 84 24.00 0 39 0 1
#> 17 24.00 0 38 0 1
#> 12.1 24.00 0 63 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.550 NA NA NA
#> 2 age, Cure model 0.00582 NA NA NA
#> 3 grade_ii, Cure model 0.234 NA NA NA
#> 4 grade_iii, Cure model 1.20 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0216 NA NA NA
#> 2 grade_ii, Survival model 1.13 NA NA NA
#> 3 grade_iii, Survival model 0.732 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.549800 0.005823 0.233742 1.199108
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 246.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.549799793 0.005822849 0.233742163 1.199108395
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.02161283 1.12994312 0.73182776
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.6289488395 0.5575125801 0.0951380584 0.0002570553 0.1875777372
#> [6] 0.6639703620 0.7858759553 0.4981893794 0.3749390979 0.8231652049
#> [11] 0.0024966783 0.9367202728 0.4636536762 0.3216651657 0.3641169741
#> [16] 0.9241380949 0.1318303297 0.2911565701 0.4074405824 0.0951380584
#> [21] 0.6289488395 0.2085091829 0.0794671216 0.8865899057 0.0570445298
#> [26] 0.4864514593 0.5818122431 0.6999046114 0.1318303297 0.8486194386
#> [31] 0.8865899057 0.7734212210 0.2085091829 0.6289488395 0.5818122431
#> [36] 0.2085091829 0.2085091829 0.3857383379 0.0328088869 0.0388773857
#> [41] 0.4636536762 0.6169177232 0.7858759553 0.0185557827 0.7364847013
#> [46] 0.0951380584 0.8231652049 0.0503723223 0.1677763447 0.4185041021
#> [51] 0.4297280651 0.1775392129 0.2491063894 0.9873404664 0.2911565701
#> [56] 0.1318303297 0.3430124315 0.7364847013 0.0715475868 0.9116024245
#> [61] 0.6639703620 0.9747544653 0.5695949748 0.7121412311 0.4297280651
#> [66] 0.0055447739 0.0147323355 0.6878372575 0.3857383379 0.0109296620
#> [71] 0.8486194386 0.0055447739 0.3216651657 0.9620892287 0.0951380584
#> [76] 0.2602599126 0.0228403634 0.4522423319 0.0024966783 0.0570445298
#> [81] 0.9367202728 0.7121412311 0.8486194386 0.0228403634 0.1583067412
#> [86] 0.2911565701 0.0951380584 0.5818122431 0.5216881571 0.1875777372
#> [91] 0.7610548598 0.5216881571 0.0388773857 0.0002570553 0.5454859605
#> [96] 0.2602599126 0.7858759553 0.3430124315 0.0794671216 0.2602599126
#> [101] 0.0002570553 0.5099487089 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 123 57 99 24 88 14 159 167 106 10 86 16 188
#> 13.00 14.46 21.19 23.89 18.37 12.89 10.55 15.55 16.67 10.53 23.81 8.71 16.16
#> 110 45 183 150 134 181 36 123.1 108 139 101 175 100
#> 17.56 17.42 9.24 20.33 17.81 16.46 21.19 13.00 18.29 21.49 9.97 21.91 16.07
#> 60 177 150.1 61 101.1 43 108.1 123.2 60.1 108.2 108.3 130 169
#> 13.15 12.53 20.33 10.12 9.97 12.10 18.29 13.00 13.15 18.29 18.29 16.47 22.41
#> 194 188.1 155 159.1 113 42 99.1 10.1 66 55 85 5 8
#> 22.40 16.16 13.08 10.55 22.86 12.43 21.19 10.53 22.13 19.34 16.44 16.43 18.43
#> 51 127 134.1 150.2 117 42.1 197 187 14.1 25 81 37 5.1
#> 18.23 3.53 17.81 20.33 17.46 12.43 21.60 9.92 12.89 6.32 14.06 12.52 16.43
#> 168 129 140 130.1 164 61.1 168.1 110.1 70 36.1 41 15 79
#> 23.72 23.41 12.68 16.47 23.60 10.12 23.72 17.56 7.38 21.19 18.02 22.68 16.23
#> 86.1 175.1 16.1 37.1 61.2 15.1 170 134.2 99.2 60.2 180 88.1 49
#> 23.81 21.91 8.71 12.52 10.12 22.68 19.54 17.81 21.19 13.15 14.82 18.37 12.19
#> 180.1 194.1 24.1 96 41.1 159.2 117.1 139.1 41.2 24.2 18 178 48
#> 14.82 22.40 23.89 14.54 18.02 10.55 17.46 21.49 18.02 23.89 15.21 24.00 24.00
#> 126 27 146 185 132 12 174 2 172 20 152 82 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 196 132.1 31 34 54 28 33 2.1 138 1 182 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.1 83 27.1 47.1 131 191 83.1 163 143 109 116 135 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.2 94 176 44 82.1 172.1 71 138.1 38 33.1 198 173.1 172.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146.1 9 120 186 34.1 44.1 185.1 104 98 33.2 118 147 38.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.1 165.1 47.2 191.1 87 71.2 143.1 147.1 87.1 11 161 71.3 20.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 144 186.1 84 17 12.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[14]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004151961 0.274684442 0.061548937
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -2.0098287 0.0309481 0.4282538
#> grade_iii, Cure model
#> 1.3985110
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 61 10.12 1 36 0 1
#> 107 11.18 1 54 1 0
#> 40 18.00 1 28 1 0
#> 40.1 18.00 1 28 1 0
#> 63 22.77 1 31 1 0
#> 105 19.75 1 60 0 0
#> 51 18.23 1 83 0 1
#> 56 12.21 1 60 0 0
#> 15 22.68 1 48 0 0
#> 108 18.29 1 39 0 1
#> 139 21.49 1 63 1 0
#> 154 12.63 1 20 1 0
#> 86 23.81 1 58 0 1
#> 117 17.46 1 26 0 1
#> 50 10.02 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 77 7.27 1 67 0 1
#> 159 10.55 1 50 0 1
#> 89.1 11.44 1 NA 0 0
#> 108.1 18.29 1 39 0 1
#> 129 23.41 1 53 1 0
#> 90 20.94 1 50 0 1
#> 170 19.54 1 43 0 1
#> 41 18.02 1 40 1 0
#> 52 10.42 1 52 0 1
#> 199 19.81 1 NA 0 1
#> 8 18.43 1 32 0 0
#> 29 15.45 1 68 1 0
#> 106 16.67 1 49 1 0
#> 100 16.07 1 60 0 0
#> 25 6.32 1 34 1 0
#> 97 19.14 1 65 0 1
#> 170.1 19.54 1 43 0 1
#> 99 21.19 1 38 0 1
#> 158 20.14 1 74 1 0
#> 195 11.76 1 NA 1 0
#> 16 8.71 1 71 0 1
#> 189 10.51 1 NA 1 0
#> 40.2 18.00 1 28 1 0
#> 56.1 12.21 1 60 0 0
#> 188 16.16 1 46 0 1
#> 99.1 21.19 1 38 0 1
#> 117.1 17.46 1 26 0 1
#> 170.2 19.54 1 43 0 1
#> 51.1 18.23 1 83 0 1
#> 39 15.59 1 37 0 1
#> 68 20.62 1 44 0 0
#> 136 21.83 1 43 0 1
#> 127 3.53 1 62 0 1
#> 188.1 16.16 1 46 0 1
#> 59 10.16 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 45 17.42 1 54 0 1
#> 187 9.92 1 39 1 0
#> 194 22.40 1 38 0 1
#> 37 12.52 1 57 1 0
#> 55 19.34 1 69 0 1
#> 194.1 22.40 1 38 0 1
#> 190 20.81 1 42 1 0
#> 111 17.45 1 47 0 1
#> 127.1 3.53 1 62 0 1
#> 4 17.64 1 NA 0 1
#> 110 17.56 1 65 0 1
#> 114 13.68 1 NA 0 0
#> 139.1 21.49 1 63 1 0
#> 15.1 22.68 1 48 0 0
#> 167 15.55 1 56 1 0
#> 110.1 17.56 1 65 0 1
#> 36 21.19 1 48 0 1
#> 42 12.43 1 49 0 1
#> 56.2 12.21 1 60 0 0
#> 129.1 23.41 1 53 1 0
#> 150 20.33 1 48 0 0
#> 70 7.38 1 30 1 0
#> 36.1 21.19 1 48 0 1
#> 86.1 23.81 1 58 0 1
#> 5 16.43 1 51 0 1
#> 43 12.10 1 61 0 1
#> 130 16.47 1 53 0 1
#> 167.1 15.55 1 56 1 0
#> 164 23.60 1 76 0 1
#> 37.1 12.52 1 57 1 0
#> 183 9.24 1 67 1 0
#> 134 17.81 1 47 1 0
#> 43.1 12.10 1 61 0 1
#> 105.1 19.75 1 60 0 0
#> 51.2 18.23 1 83 0 1
#> 76 19.22 1 54 0 1
#> 179 18.63 1 42 0 0
#> 145 10.07 1 65 1 0
#> 158.1 20.14 1 74 1 0
#> 57 14.46 1 45 0 1
#> 79 16.23 1 54 1 0
#> 37.2 12.52 1 57 1 0
#> 179.1 18.63 1 42 0 0
#> 184 17.77 1 38 0 0
#> 52.1 10.42 1 52 0 1
#> 96 14.54 1 33 0 1
#> 183.1 9.24 1 67 1 0
#> 195.1 11.76 1 NA 1 0
#> 68.1 20.62 1 44 0 0
#> 159.1 10.55 1 50 0 1
#> 164.1 23.60 1 76 0 1
#> 127.2 3.53 1 62 0 1
#> 180 14.82 1 37 0 0
#> 181 16.46 1 45 0 1
#> 58 19.34 1 39 0 0
#> 189.1 10.51 1 NA 1 0
#> 66 22.13 1 53 0 0
#> 61.1 10.12 1 36 0 1
#> 13 14.34 1 54 0 1
#> 86.2 23.81 1 58 0 1
#> 185 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 20 24.00 0 46 1 0
#> 94 24.00 0 51 0 1
#> 109 24.00 0 48 0 0
#> 48 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 103 24.00 0 56 1 0
#> 3 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 185.1 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 174 24.00 0 49 1 0
#> 75 24.00 0 21 1 0
#> 48.1 24.00 0 31 1 0
#> 94.1 24.00 0 51 0 1
#> 80 24.00 0 41 0 0
#> 148 24.00 0 61 1 0
#> 87 24.00 0 27 0 0
#> 120 24.00 0 68 0 1
#> 116 24.00 0 58 0 1
#> 156 24.00 0 50 1 0
#> 138 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 80.1 24.00 0 41 0 0
#> 182 24.00 0 35 0 0
#> 46 24.00 0 71 0 0
#> 176 24.00 0 43 0 1
#> 118 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 28 24.00 0 67 1 0
#> 163 24.00 0 66 0 0
#> 35 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 94.2 24.00 0 51 0 1
#> 138.1 24.00 0 44 1 0
#> 3.1 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 38 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 162.1 24.00 0 51 0 0
#> 80.2 24.00 0 41 0 0
#> 141 24.00 0 44 1 0
#> 80.3 24.00 0 41 0 0
#> 11 24.00 0 42 0 1
#> 109.1 24.00 0 48 0 0
#> 198 24.00 0 66 0 1
#> 1 24.00 0 23 1 0
#> 109.2 24.00 0 48 0 0
#> 35.1 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 116.1 24.00 0 58 0 1
#> 148.1 24.00 0 61 1 0
#> 54 24.00 0 53 1 0
#> 94.3 24.00 0 51 0 1
#> 98 24.00 0 34 1 0
#> 87.1 24.00 0 27 0 0
#> 174.1 24.00 0 49 1 0
#> 115 24.00 0 NA 1 0
#> 75.1 24.00 0 21 1 0
#> 38.1 24.00 0 31 1 0
#> 135.1 24.00 0 58 1 0
#> 44 24.00 0 56 0 0
#> 191 24.00 0 60 0 1
#> 173.1 24.00 0 19 0 1
#> 12 24.00 0 63 0 0
#> 47 24.00 0 38 0 1
#> 161.1 24.00 0 45 0 0
#> 116.2 24.00 0 58 0 1
#> 84 24.00 0 39 0 1
#> 143 24.00 0 51 0 0
#> 38.2 24.00 0 31 1 0
#> 47.1 24.00 0 38 0 1
#> 174.2 24.00 0 49 1 0
#> 162.2 24.00 0 51 0 0
#> 95 24.00 0 68 0 1
#> 172 24.00 0 41 0 0
#> 172.1 24.00 0 41 0 0
#> 33.1 24.00 0 53 0 0
#> 9 24.00 0 31 1 0
#> 176.1 24.00 0 43 0 1
#> 80.4 24.00 0 41 0 0
#> 11.1 24.00 0 42 0 1
#> 53 24.00 0 32 0 1
#> 118.1 24.00 0 44 1 0
#> 2.1 24.00 0 9 0 0
#> 28.1 24.00 0 67 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -2.01 NA NA NA
#> 2 age, Cure model 0.0309 NA NA NA
#> 3 grade_ii, Cure model 0.428 NA NA NA
#> 4 grade_iii, Cure model 1.40 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00415 NA NA NA
#> 2 grade_ii, Survival model 0.275 NA NA NA
#> 3 grade_iii, Survival model 0.0615 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -2.00983 0.03095 0.42825 1.39851
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.6
#> Residual Deviance: 234.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -2.0098287 0.0309481 0.4282538 1.3985110
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004151961 0.274684442 0.061548937
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.860557948 0.807265912 0.413765664 0.413765664 0.058931068 0.237060635
#> [7] 0.373322175 0.754602042 0.067546884 0.353339478 0.120035922 0.702423546
#> [13] 0.007871309 0.484003412 0.946356240 0.817934517 0.353339478 0.042618549
#> [19] 0.171944275 0.256007318 0.403481329 0.839207515 0.343258120 0.649757206
#> [25] 0.535249020 0.607933704 0.957132639 0.313508072 0.256007318 0.137786038
#> [31] 0.218442684 0.924831088 0.413765664 0.754602042 0.587202271 0.137786038
#> [37] 0.484003412 0.256007318 0.373322175 0.618429139 0.190553393 0.110789866
#> [43] 0.967891736 0.587202271 0.514559792 0.524889101 0.892715696 0.084424611
#> [49] 0.712963753 0.284237089 0.084424611 0.181273970 0.504287534 0.967891736
#> [55] 0.463757881 0.120035922 0.067546884 0.628940269 0.463757881 0.137786038
#> [61] 0.744066761 0.754602042 0.042618549 0.208953409 0.935603690 0.137786038
#> [67] 0.007871309 0.566364970 0.786055284 0.545594161 0.628940269 0.026038127
#> [73] 0.712963753 0.903462845 0.443488171 0.786055284 0.237060635 0.373322175
#> [79] 0.303612477 0.323462779 0.881953083 0.218442684 0.681300312 0.576788490
#> [85] 0.712963753 0.323462779 0.453606497 0.839207515 0.670770003 0.903462845
#> [91] 0.190553393 0.817934517 0.026038127 0.967891736 0.660251699 0.555968140
#> [97] 0.284237089 0.101628611 0.860557948 0.691849826 0.007871309 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 61 107 40 40.1 63 105 51 56 15 108 139 154 86
#> 10.12 11.18 18.00 18.00 22.77 19.75 18.23 12.21 22.68 18.29 21.49 12.63 23.81
#> 117 77 159 108.1 129 90 170 41 52 8 29 106 100
#> 17.46 7.27 10.55 18.29 23.41 20.94 19.54 18.02 10.42 18.43 15.45 16.67 16.07
#> 25 97 170.1 99 158 16 40.2 56.1 188 99.1 117.1 170.2 51.1
#> 6.32 19.14 19.54 21.19 20.14 8.71 18.00 12.21 16.16 21.19 17.46 19.54 18.23
#> 39 68 136 127 188.1 30 45 187 194 37 55 194.1 190
#> 15.59 20.62 21.83 3.53 16.16 17.43 17.42 9.92 22.40 12.52 19.34 22.40 20.81
#> 111 127.1 110 139.1 15.1 167 110.1 36 42 56.2 129.1 150 70
#> 17.45 3.53 17.56 21.49 22.68 15.55 17.56 21.19 12.43 12.21 23.41 20.33 7.38
#> 36.1 86.1 5 43 130 167.1 164 37.1 183 134 43.1 105.1 51.2
#> 21.19 23.81 16.43 12.10 16.47 15.55 23.60 12.52 9.24 17.81 12.10 19.75 18.23
#> 76 179 145 158.1 57 79 37.2 179.1 184 52.1 96 183.1 68.1
#> 19.22 18.63 10.07 20.14 14.46 16.23 12.52 18.63 17.77 10.42 14.54 9.24 20.62
#> 159.1 164.1 127.2 180 181 58 66 61.1 13 86.2 185 162 161
#> 10.55 23.60 3.53 14.82 16.46 19.34 22.13 10.12 14.34 23.81 24.00 24.00 24.00
#> 20 94 109 48 122 103 3 34 185.1 173 174 75 48.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 80 148 87 120 116 156 138 33 80.1 182 46 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 135 28 163 35 2 94.2 138.1 3.1 83 38 146 162.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80.2 141 80.3 11 109.1 198 1 109.2 35.1 21 116.1 148.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.3 98 87.1 174.1 75.1 38.1 135.1 44 191 173.1 12 47 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.2 84 143 38.2 47.1 174.2 162.2 95 172 172.1 33.1 9 176.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80.4 11.1 53 118.1 2.1 28.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[15]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00838762 0.48378138 0.63313183
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.76716566 0.01751951 0.06968239
#> grade_iii, Cure model
#> 0.49279288
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 155 13.08 1 26 0 0
#> 45 17.42 1 54 0 1
#> 150 20.33 1 48 0 0
#> 108 18.29 1 39 0 1
#> 58 19.34 1 39 0 0
#> 66 22.13 1 53 0 0
#> 50 10.02 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 60 13.15 1 38 1 0
#> 85 16.44 1 36 0 0
#> 158 20.14 1 74 1 0
#> 155.1 13.08 1 26 0 0
#> 69 23.23 1 25 0 1
#> 90 20.94 1 50 0 1
#> 78 23.88 1 43 0 0
#> 77 7.27 1 67 0 1
#> 134 17.81 1 47 1 0
#> 180 14.82 1 37 0 0
#> 43 12.10 1 61 0 1
#> 96 14.54 1 33 0 1
#> 78.1 23.88 1 43 0 0
#> 167 15.55 1 56 1 0
#> 42 12.43 1 49 0 1
#> 128 20.35 1 35 0 1
#> 106 16.67 1 49 1 0
#> 61 10.12 1 36 0 1
#> 42.1 12.43 1 49 0 1
#> 179 18.63 1 42 0 0
#> 194 22.40 1 38 0 1
#> 100 16.07 1 60 0 0
#> 129 23.41 1 53 1 0
#> 150.1 20.33 1 48 0 0
#> 128.1 20.35 1 35 0 1
#> 29 15.45 1 68 1 0
#> 97 19.14 1 65 0 1
#> 199.1 19.81 1 NA 0 1
#> 111 17.45 1 47 0 1
#> 91 5.33 1 61 0 1
#> 159 10.55 1 50 0 1
#> 192 16.44 1 31 1 0
#> 8 18.43 1 32 0 0
#> 66.1 22.13 1 53 0 0
#> 41 18.02 1 40 1 0
#> 70 7.38 1 30 1 0
#> 167.1 15.55 1 56 1 0
#> 52 10.42 1 52 0 1
#> 188 16.16 1 46 0 1
#> 52.1 10.42 1 52 0 1
#> 168 23.72 1 70 0 0
#> 24 23.89 1 38 0 0
#> 42.2 12.43 1 49 0 1
#> 190 20.81 1 42 1 0
#> 8.1 18.43 1 32 0 0
#> 197 21.60 1 69 1 0
#> 180.1 14.82 1 37 0 0
#> 166 19.98 1 48 0 0
#> 49 12.19 1 48 1 0
#> 107 11.18 1 54 1 0
#> 8.2 18.43 1 32 0 0
#> 192.1 16.44 1 31 1 0
#> 40 18.00 1 28 1 0
#> 164 23.60 1 76 0 1
#> 192.2 16.44 1 31 1 0
#> 179.1 18.63 1 42 0 0
#> 56 12.21 1 60 0 0
#> 99 21.19 1 38 0 1
#> 170 19.54 1 43 0 1
#> 60.1 13.15 1 38 1 0
#> 88 18.37 1 47 0 0
#> 197.1 21.60 1 69 1 0
#> 5 16.43 1 51 0 1
#> 32 20.90 1 37 1 0
#> 68 20.62 1 44 0 0
#> 93 10.33 1 52 0 1
#> 60.2 13.15 1 38 1 0
#> 66.2 22.13 1 53 0 0
#> 49.1 12.19 1 48 1 0
#> 32.1 20.90 1 37 1 0
#> 155.2 13.08 1 26 0 0
#> 6 15.64 1 39 0 0
#> 39 15.59 1 37 0 1
#> 61.1 10.12 1 36 0 1
#> 150.2 20.33 1 48 0 0
#> 199.2 19.81 1 NA 0 1
#> 157 15.10 1 47 0 0
#> 14 12.89 1 21 0 0
#> 169 22.41 1 46 0 0
#> 76 19.22 1 54 0 1
#> 197.2 21.60 1 69 1 0
#> 49.2 12.19 1 48 1 0
#> 195 11.76 1 NA 1 0
#> 169.1 22.41 1 46 0 0
#> 97.1 19.14 1 65 0 1
#> 145 10.07 1 65 1 0
#> 189 10.51 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 189.1 10.51 1 NA 1 0
#> 39.1 15.59 1 37 0 1
#> 192.3 16.44 1 31 1 0
#> 39.2 15.59 1 37 0 1
#> 158.1 20.14 1 74 1 0
#> 88.1 18.37 1 47 0 0
#> 29.1 15.45 1 68 1 0
#> 16 8.71 1 71 0 1
#> 97.2 19.14 1 65 0 1
#> 58.1 19.34 1 39 0 0
#> 108.1 18.29 1 39 0 1
#> 40.1 18.00 1 28 1 0
#> 57 14.46 1 45 0 1
#> 10 10.53 1 34 0 0
#> 197.3 21.60 1 69 1 0
#> 63 22.77 1 31 1 0
#> 21 24.00 0 47 0 0
#> 75 24.00 0 21 1 0
#> 35 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 141 24.00 0 44 1 0
#> 176 24.00 0 43 0 1
#> 156 24.00 0 50 1 0
#> 160 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 132 24.00 0 55 0 0
#> 148 24.00 0 61 1 0
#> 98 24.00 0 34 1 0
#> 35.1 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 146 24.00 0 63 1 0
#> 7.1 24.00 0 37 1 0
#> 83 24.00 0 6 0 0
#> 119 24.00 0 17 0 0
#> 84 24.00 0 39 0 1
#> 148.1 24.00 0 61 1 0
#> 12 24.00 0 63 0 0
#> 102 24.00 0 49 0 0
#> 12.1 24.00 0 63 0 0
#> 53 24.00 0 32 0 1
#> 71 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 120 24.00 0 68 0 1
#> 31.1 24.00 0 36 0 1
#> 71.1 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 119.1 24.00 0 17 0 0
#> 33 24.00 0 53 0 0
#> 138 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 82 24.00 0 34 0 0
#> 87 24.00 0 27 0 0
#> 151 24.00 0 42 0 0
#> 83.1 24.00 0 6 0 0
#> 21.1 24.00 0 47 0 0
#> 98.1 24.00 0 34 1 0
#> 48 24.00 0 31 1 0
#> 9.1 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 47 24.00 0 38 0 1
#> 142 24.00 0 53 0 0
#> 165 24.00 0 47 0 0
#> 19.1 24.00 0 57 0 1
#> 144 24.00 0 28 0 1
#> 3 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 82.1 24.00 0 34 0 0
#> 122 24.00 0 66 0 0
#> 148.2 24.00 0 61 1 0
#> 75.1 24.00 0 21 1 0
#> 132.1 24.00 0 55 0 0
#> 126.1 24.00 0 48 0 0
#> 9.2 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 148.3 24.00 0 61 1 0
#> 64 24.00 0 43 0 0
#> 160.1 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 103 24.00 0 56 1 0
#> 152 24.00 0 36 0 1
#> 19.2 24.00 0 57 0 1
#> 80 24.00 0 41 0 0
#> 112 24.00 0 61 0 0
#> 131 24.00 0 66 0 0
#> 47.1 24.00 0 38 0 1
#> 3.1 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 185 24.00 0 44 1 0
#> 75.2 24.00 0 21 1 0
#> 53.1 24.00 0 32 0 1
#> 147 24.00 0 76 1 0
#> 138.1 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 152.1 24.00 0 36 0 1
#> 83.2 24.00 0 6 0 0
#> 47.2 24.00 0 38 0 1
#> 65 24.00 0 57 1 0
#> 87.1 24.00 0 27 0 0
#> 87.2 24.00 0 27 0 0
#> 2 24.00 0 9 0 0
#> 82.2 24.00 0 34 0 0
#> 151.1 24.00 0 42 0 0
#> 48.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.767 NA NA NA
#> 2 age, Cure model 0.0175 NA NA NA
#> 3 grade_ii, Cure model 0.0697 NA NA NA
#> 4 grade_iii, Cure model 0.493 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00839 NA NA NA
#> 2 grade_ii, Survival model 0.484 NA NA NA
#> 3 grade_iii, Survival model 0.633 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.76717 0.01752 0.06968 0.49279
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 257.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.76716566 0.01751951 0.06968239 0.49279288
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00838762 0.48378138 0.63313183
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.762830891 0.513424345 0.245923142 0.443076564 0.313777063 0.102198285
#> [7] 0.734462718 0.533307420 0.274362887 0.762830891 0.055111807 0.178703653
#> [13] 0.009103990 0.981217911 0.493396867 0.695777022 0.867503217 0.715128775
#> [19] 0.009103990 0.647910396 0.801068905 0.227307782 0.523373008 0.934199107
#> [25] 0.801068905 0.372646515 0.092672382 0.599955907 0.044575747 0.245923142
#> [31] 0.227307782 0.666985110 0.343665935 0.503437478 0.990614705 0.886640218
#> [37] 0.533307420 0.392536873 0.102198285 0.463295883 0.971814476 0.647910396
#> [43] 0.905750156 0.590268831 0.905750156 0.023369807 0.002300976 0.801068905
#> [49] 0.207765902 0.392536873 0.130837672 0.695777022 0.293842192 0.839068305
#> [55] 0.877073352 0.392536873 0.533307420 0.473482405 0.033951733 0.533307420
#> [61] 0.372646515 0.829453030 0.168582000 0.303860808 0.734462718 0.422521664
#> [67] 0.130837672 0.580536951 0.188690687 0.217469077 0.924697635 0.734462718
#> [73] 0.102198285 0.839068305 0.188690687 0.762830891 0.609705233 0.619498251
#> [79] 0.934199107 0.245923142 0.686105207 0.791407387 0.073928911 0.333641243
#> [85] 0.130837672 0.839068305 0.073928911 0.343665935 0.952956395 0.619498251
#> [91] 0.533307420 0.619498251 0.274362887 0.422521664 0.666985110 0.962387206
#> [97] 0.343665935 0.313777063 0.443076564 0.473482405 0.724814527 0.896182548
#> [103] 0.130837672 0.064690359 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 155 45 150 108 58 66 60 85 158 155.1 69 90 78
#> 13.08 17.42 20.33 18.29 19.34 22.13 13.15 16.44 20.14 13.08 23.23 20.94 23.88
#> 77 134 180 43 96 78.1 167 42 128 106 61 42.1 179
#> 7.27 17.81 14.82 12.10 14.54 23.88 15.55 12.43 20.35 16.67 10.12 12.43 18.63
#> 194 100 129 150.1 128.1 29 97 111 91 159 192 8 66.1
#> 22.40 16.07 23.41 20.33 20.35 15.45 19.14 17.45 5.33 10.55 16.44 18.43 22.13
#> 41 70 167.1 52 188 52.1 168 24 42.2 190 8.1 197 180.1
#> 18.02 7.38 15.55 10.42 16.16 10.42 23.72 23.89 12.43 20.81 18.43 21.60 14.82
#> 166 49 107 8.2 192.1 40 164 192.2 179.1 56 99 170 60.1
#> 19.98 12.19 11.18 18.43 16.44 18.00 23.60 16.44 18.63 12.21 21.19 19.54 13.15
#> 88 197.1 5 32 68 93 60.2 66.2 49.1 32.1 155.2 6 39
#> 18.37 21.60 16.43 20.90 20.62 10.33 13.15 22.13 12.19 20.90 13.08 15.64 15.59
#> 61.1 150.2 157 14 169 76 197.2 49.2 169.1 97.1 145 39.1 192.3
#> 10.12 20.33 15.10 12.89 22.41 19.22 21.60 12.19 22.41 19.14 10.07 15.59 16.44
#> 39.2 158.1 88.1 29.1 16 97.2 58.1 108.1 40.1 57 10 197.3 63
#> 15.59 20.14 18.37 15.45 8.71 19.14 19.34 18.29 18.00 14.46 10.53 21.60 22.77
#> 21 75 35 31 141 176 156 160 7 132 148 98 35.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 7.1 83 119 84 148.1 12 102 12.1 53 71 9 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 31.1 71.1 62 119.1 33 138 19 82 87 151 83.1 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.1 48 9.1 11 47 142 165 19.1 144 3 198 82.1 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.2 75.1 132.1 126.1 9.2 193 148.3 64 160.1 135 103 152 19.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 112 131 47.1 3.1 74 185 75.2 53.1 147 138.1 191 152.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83.2 47.2 65 87.1 87.2 2 82.2 151.1 48.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[16]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002805582 0.661724858 0.381204852
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.73866374 0.01991382 -0.23206589
#> grade_iii, Cure model
#> 0.21443374
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 157 15.10 1 47 0 0
#> 127 3.53 1 62 0 1
#> 36 21.19 1 48 0 1
#> 168 23.72 1 70 0 0
#> 58 19.34 1 39 0 0
#> 168.1 23.72 1 70 0 0
#> 52 10.42 1 52 0 1
#> 32 20.90 1 37 1 0
#> 70 7.38 1 30 1 0
#> 25 6.32 1 34 1 0
#> 97 19.14 1 65 0 1
#> 130 16.47 1 53 0 1
#> 199 19.81 1 NA 0 1
#> 145 10.07 1 65 1 0
#> 114 13.68 1 NA 0 0
#> 195 11.76 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 14 12.89 1 21 0 0
#> 190 20.81 1 42 1 0
#> 96 14.54 1 33 0 1
#> 58.1 19.34 1 39 0 0
#> 78 23.88 1 43 0 0
#> 164 23.60 1 76 0 1
#> 133 14.65 1 57 0 0
#> 32.1 20.90 1 37 1 0
#> 123 13.00 1 44 1 0
#> 91 5.33 1 61 0 1
#> 105 19.75 1 60 0 0
#> 29 15.45 1 68 1 0
#> 70.1 7.38 1 30 1 0
#> 86 23.81 1 58 0 1
#> 110 17.56 1 65 0 1
#> 10 10.53 1 34 0 0
#> 181 16.46 1 45 0 1
#> 184 17.77 1 38 0 0
#> 81 14.06 1 34 0 0
#> 23 16.92 1 61 0 0
#> 183 9.24 1 67 1 0
#> 79 16.23 1 54 1 0
#> 181.1 16.46 1 45 0 1
#> 29.1 15.45 1 68 1 0
#> 63 22.77 1 31 1 0
#> 56 12.21 1 60 0 0
#> 97.1 19.14 1 65 0 1
#> 177 12.53 1 75 0 0
#> 90 20.94 1 50 0 1
#> 149 8.37 1 33 1 0
#> 177.1 12.53 1 75 0 0
#> 181.2 16.46 1 45 0 1
#> 59 10.16 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 189 10.51 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 79.1 16.23 1 54 1 0
#> 190.1 20.81 1 42 1 0
#> 76 19.22 1 54 0 1
#> 153 21.33 1 55 1 0
#> 181.3 16.46 1 45 0 1
#> 169 22.41 1 46 0 0
#> 57 14.46 1 45 0 1
#> 61 10.12 1 36 0 1
#> 125 15.65 1 67 1 0
#> 89 11.44 1 NA 0 0
#> 18 15.21 1 49 1 0
#> 41 18.02 1 40 1 0
#> 78.1 23.88 1 43 0 0
#> 133.1 14.65 1 57 0 0
#> 169.1 22.41 1 46 0 0
#> 136 21.83 1 43 0 1
#> 30 17.43 1 78 0 0
#> 133.2 14.65 1 57 0 0
#> 184.1 17.77 1 38 0 0
#> 192 16.44 1 31 1 0
#> 85 16.44 1 36 0 0
#> 188 16.16 1 46 0 1
#> 188.1 16.16 1 46 0 1
#> 56.1 12.21 1 60 0 0
#> 111 17.45 1 47 0 1
#> 168.2 23.72 1 70 0 0
#> 117 17.46 1 26 0 1
#> 61.1 10.12 1 36 0 1
#> 124 9.73 1 NA 1 0
#> 30.1 17.43 1 78 0 0
#> 150 20.33 1 48 0 0
#> 61.2 10.12 1 36 0 1
#> 181.4 16.46 1 45 0 1
#> 105.1 19.75 1 60 0 0
#> 60 13.15 1 38 1 0
#> 43 12.10 1 61 0 1
#> 37.1 12.52 1 57 1 0
#> 66 22.13 1 53 0 0
#> 39 15.59 1 37 0 1
#> 166 19.98 1 48 0 0
#> 60.1 13.15 1 38 1 0
#> 25.1 6.32 1 34 1 0
#> 100 16.07 1 60 0 0
#> 159 10.55 1 50 0 1
#> 139 21.49 1 63 1 0
#> 128 20.35 1 35 0 1
#> 30.2 17.43 1 78 0 0
#> 57.1 14.46 1 45 0 1
#> 100.1 16.07 1 60 0 0
#> 167 15.55 1 56 1 0
#> 18.1 15.21 1 49 1 0
#> 13 14.34 1 54 0 1
#> 14.1 12.89 1 21 0 0
#> 181.5 16.46 1 45 0 1
#> 108 18.29 1 39 0 1
#> 179 18.63 1 42 0 0
#> 55 19.34 1 69 0 1
#> 70.2 7.38 1 30 1 0
#> 43.1 12.10 1 61 0 1
#> 19 24.00 0 57 0 1
#> 137 24.00 0 45 1 0
#> 84 24.00 0 39 0 1
#> 148 24.00 0 61 1 0
#> 156 24.00 0 50 1 0
#> 186 24.00 0 45 1 0
#> 160 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 75 24.00 0 21 1 0
#> 67 24.00 0 25 0 0
#> 143 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 19.1 24.00 0 57 0 1
#> 17 24.00 0 38 0 1
#> 27 24.00 0 63 1 0
#> 64 24.00 0 43 0 0
#> 2 24.00 0 9 0 0
#> 104 24.00 0 50 1 0
#> 20 24.00 0 46 1 0
#> 131 24.00 0 66 0 0
#> 102 24.00 0 49 0 0
#> 44 24.00 0 56 0 0
#> 75.1 24.00 0 21 1 0
#> 94.1 24.00 0 51 0 1
#> 95 24.00 0 68 0 1
#> 3 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 102.1 24.00 0 49 0 0
#> 182 24.00 0 35 0 0
#> 165 24.00 0 47 0 0
#> 143.1 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 165.1 24.00 0 47 0 0
#> 142 24.00 0 53 0 0
#> 144 24.00 0 28 0 1
#> 119 24.00 0 17 0 0
#> 95.1 24.00 0 68 0 1
#> 174 24.00 0 49 1 0
#> 72 24.00 0 40 0 1
#> 151 24.00 0 42 0 0
#> 137.1 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 27.1 24.00 0 63 1 0
#> 27.2 24.00 0 63 1 0
#> 196 24.00 0 19 0 0
#> 144.1 24.00 0 28 0 1
#> 173 24.00 0 19 0 1
#> 191 24.00 0 60 0 1
#> 116 24.00 0 58 0 1
#> 73 24.00 0 NA 0 1
#> 34.1 24.00 0 36 0 0
#> 48 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 148.1 24.00 0 61 1 0
#> 28 24.00 0 67 1 0
#> 104.1 24.00 0 50 1 0
#> 31 24.00 0 36 0 1
#> 67.1 24.00 0 25 0 0
#> 191.1 24.00 0 60 0 1
#> 141 24.00 0 44 1 0
#> 53 24.00 0 32 0 1
#> 21 24.00 0 47 0 0
#> 196.1 24.00 0 19 0 0
#> 20.1 24.00 0 46 1 0
#> 19.2 24.00 0 57 0 1
#> 54 24.00 0 53 1 0
#> 80 24.00 0 41 0 0
#> 83 24.00 0 6 0 0
#> 2.1 24.00 0 9 0 0
#> 12 24.00 0 63 0 0
#> 74 24.00 0 43 0 1
#> 62 24.00 0 71 0 0
#> 53.1 24.00 0 32 0 1
#> 126 24.00 0 48 0 0
#> 53.2 24.00 0 32 0 1
#> 163.1 24.00 0 66 0 0
#> 137.2 24.00 0 45 1 0
#> 185 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 146 24.00 0 63 1 0
#> 62.1 24.00 0 71 0 0
#> 148.2 24.00 0 61 1 0
#> 141.1 24.00 0 44 1 0
#> 84.1 24.00 0 39 0 1
#> 116.1 24.00 0 58 0 1
#> 48.1 24.00 0 31 1 0
#> 191.2 24.00 0 60 0 1
#> 28.1 24.00 0 67 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.739 NA NA NA
#> 2 age, Cure model 0.0199 NA NA NA
#> 3 grade_ii, Cure model -0.232 NA NA NA
#> 4 grade_iii, Cure model 0.214 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00281 NA NA NA
#> 2 grade_ii, Survival model 0.662 NA NA NA
#> 3 grade_iii, Survival model 0.381 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.73866 0.01991 -0.23207 0.21443
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 257.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.73866374 0.01991382 -0.23206589 0.21443374
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002805582 0.661724858 0.381204852
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.69454692 0.99242765 0.21514808 0.05106315 0.32786647 0.05106315
#> [7] 0.89137074 0.23802708 0.94680945 0.96970189 0.36702052 0.50103396
#> [13] 0.92313986 0.10255020 0.79432593 0.25876541 0.72804483 0.32786647
#> [19] 0.01186244 0.08826222 0.70296377 0.23802708 0.78616687 0.98484197
#> [25] 0.30809307 0.66084458 0.94680945 0.03665670 0.43470176 0.88330430
#> [31] 0.51058452 0.41563090 0.76145984 0.49143551 0.93107374 0.58169950
#> [37] 0.51058452 0.66084458 0.11615078 0.84300297 0.36702052 0.81057926
#> [43] 0.22666614 0.93896687 0.81057926 0.51058452 0.82689467 0.16571753
#> [49] 0.58169950 0.25876541 0.35707730 0.20345521 0.51058452 0.12862008
#> [55] 0.73647032 0.89941786 0.63458787 0.67784008 0.40602866 0.01186244
#> [61] 0.70296377 0.12862008 0.17864528 0.46328373 0.70296377 0.41563090
#> [67] 0.56363091 0.56363091 0.59940212 0.59940212 0.84300297 0.45381864
#> [73] 0.05106315 0.44429731 0.89941786 0.46328373 0.28823507 0.89941786
#> [79] 0.51058452 0.30809307 0.76981304 0.85915911 0.82689467 0.15290382
#> [85] 0.64339121 0.29814323 0.76981304 0.96970189 0.61695612 0.87524455
#> [91] 0.19130094 0.27836967 0.46328373 0.73647032 0.61695612 0.65215622
#> [97] 0.67784008 0.75311496 0.79432593 0.51058452 0.39625719 0.38640991
#> [103] 0.32786647 0.94680945 0.85915911 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 157 127 36 168 58 168.1 52 32 70 25 97 130 145
#> 15.10 3.53 21.19 23.72 19.34 23.72 10.42 20.90 7.38 6.32 19.14 16.47 10.07
#> 69 14 190 96 58.1 78 164 133 32.1 123 91 105 29
#> 23.23 12.89 20.81 14.54 19.34 23.88 23.60 14.65 20.90 13.00 5.33 19.75 15.45
#> 70.1 86 110 10 181 184 81 23 183 79 181.1 29.1 63
#> 7.38 23.81 17.56 10.53 16.46 17.77 14.06 16.92 9.24 16.23 16.46 15.45 22.77
#> 56 97.1 177 90 149 177.1 181.2 37 175 79.1 190.1 76 153
#> 12.21 19.14 12.53 20.94 8.37 12.53 16.46 12.52 21.91 16.23 20.81 19.22 21.33
#> 181.3 169 57 61 125 18 41 78.1 133.1 169.1 136 30 133.2
#> 16.46 22.41 14.46 10.12 15.65 15.21 18.02 23.88 14.65 22.41 21.83 17.43 14.65
#> 184.1 192 85 188 188.1 56.1 111 168.2 117 61.1 30.1 150 61.2
#> 17.77 16.44 16.44 16.16 16.16 12.21 17.45 23.72 17.46 10.12 17.43 20.33 10.12
#> 181.4 105.1 60 43 37.1 66 39 166 60.1 25.1 100 159 139
#> 16.46 19.75 13.15 12.10 12.52 22.13 15.59 19.98 13.15 6.32 16.07 10.55 21.49
#> 128 30.2 57.1 100.1 167 18.1 13 14.1 181.5 108 179 55 70.2
#> 20.35 17.43 14.46 16.07 15.55 15.21 14.34 12.89 16.46 18.29 18.63 19.34 7.38
#> 43.1 19 137 84 148 156 186 160 176 75 67 143 94
#> 12.10 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.1 17 27 64 2 104 20 131 102 44 75.1 94.1 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 34 102.1 182 165 143.1 165.1 142 144 119 95.1 174 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 137.1 163 27.1 27.2 196 144.1 173 191 116 34.1 48 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.1 28 104.1 31 67.1 191.1 141 53 21 196.1 20.1 19.2 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 83 2.1 12 74 62 53.1 126 53.2 163.1 137.2 185 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 62.1 148.2 141.1 84.1 116.1 48.1 191.2 28.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[17]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004447462 0.562281139 0.323225383
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.94488472 0.02478228 -0.33124764
#> grade_iii, Cure model
#> 0.23894866
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 194 22.40 1 38 0 1
#> 114 13.68 1 NA 0 0
#> 127 3.53 1 62 0 1
#> 29 15.45 1 68 1 0
#> 89 11.44 1 NA 0 0
#> 99 21.19 1 38 0 1
#> 8 18.43 1 32 0 0
#> 195 11.76 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 100 16.07 1 60 0 0
#> 145 10.07 1 65 1 0
#> 179.1 18.63 1 42 0 0
#> 61 10.12 1 36 0 1
#> 76 19.22 1 54 0 1
#> 100.1 16.07 1 60 0 0
#> 56 12.21 1 60 0 0
#> 50 10.02 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 133 14.65 1 57 0 0
#> 85 16.44 1 36 0 0
#> 171 16.57 1 41 0 1
#> 51 18.23 1 83 0 1
#> 197 21.60 1 69 1 0
#> 14 12.89 1 21 0 0
#> 158 20.14 1 74 1 0
#> 192 16.44 1 31 1 0
#> 134 17.81 1 47 1 0
#> 107 11.18 1 54 1 0
#> 183 9.24 1 67 1 0
#> 167 15.55 1 56 1 0
#> 63 22.77 1 31 1 0
#> 14.1 12.89 1 21 0 0
#> 164 23.60 1 76 0 1
#> 169 22.41 1 46 0 0
#> 99.1 21.19 1 38 0 1
#> 99.2 21.19 1 38 0 1
#> 166 19.98 1 48 0 0
#> 168 23.72 1 70 0 0
#> 197.1 21.60 1 69 1 0
#> 187 9.92 1 39 1 0
#> 181 16.46 1 45 0 1
#> 154 12.63 1 20 1 0
#> 92 22.92 1 47 0 1
#> 136 21.83 1 43 0 1
#> 77 7.27 1 67 0 1
#> 107.1 11.18 1 54 1 0
#> 89.1 11.44 1 NA 0 0
#> 140 12.68 1 59 1 0
#> 85.1 16.44 1 36 0 0
#> 99.3 21.19 1 38 0 1
#> 57 14.46 1 45 0 1
#> 68 20.62 1 44 0 0
#> 51.1 18.23 1 83 0 1
#> 5 16.43 1 51 0 1
#> 43 12.10 1 61 0 1
#> 93 10.33 1 52 0 1
#> 61.1 10.12 1 36 0 1
#> 167.1 15.55 1 56 1 0
#> 169.1 22.41 1 46 0 0
#> 56.1 12.21 1 60 0 0
#> 58 19.34 1 39 0 0
#> 127.1 3.53 1 62 0 1
#> 85.2 16.44 1 36 0 0
#> 107.2 11.18 1 54 1 0
#> 189 10.51 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 166.1 19.98 1 48 0 0
#> 88 18.37 1 47 0 0
#> 79 16.23 1 54 1 0
#> 90 20.94 1 50 0 1
#> 49 12.19 1 48 1 0
#> 60 13.15 1 38 1 0
#> 149 8.37 1 33 1 0
#> 155 13.08 1 26 0 0
#> 101 9.97 1 10 0 1
#> 6 15.64 1 39 0 0
#> 192.1 16.44 1 31 1 0
#> 195.1 11.76 1 NA 1 0
#> 63.1 22.77 1 31 1 0
#> 18 15.21 1 49 1 0
#> 29.1 15.45 1 68 1 0
#> 88.1 18.37 1 47 0 0
#> 133.1 14.65 1 57 0 0
#> 108 18.29 1 39 0 1
#> 41 18.02 1 40 1 0
#> 169.2 22.41 1 46 0 0
#> 15 22.68 1 48 0 0
#> 168.1 23.72 1 70 0 0
#> 125 15.65 1 67 1 0
#> 51.2 18.23 1 83 0 1
#> 105.1 19.75 1 60 0 0
#> 26 15.77 1 49 0 1
#> 166.2 19.98 1 48 0 0
#> 5.1 16.43 1 51 0 1
#> 166.3 19.98 1 48 0 0
#> 183.1 9.24 1 67 1 0
#> 32 20.90 1 37 1 0
#> 43.1 12.10 1 61 0 1
#> 66 22.13 1 53 0 0
#> 139 21.49 1 63 1 0
#> 139.1 21.49 1 63 1 0
#> 81 14.06 1 34 0 0
#> 6.1 15.64 1 39 0 0
#> 76.1 19.22 1 54 0 1
#> 89.2 11.44 1 NA 0 0
#> 167.2 15.55 1 56 1 0
#> 170 19.54 1 43 0 1
#> 166.4 19.98 1 48 0 0
#> 51.3 18.23 1 83 0 1
#> 124 9.73 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 184 17.77 1 38 0 0
#> 135 24.00 0 58 1 0
#> 11 24.00 0 42 0 1
#> 98 24.00 0 34 1 0
#> 44 24.00 0 56 0 0
#> 47 24.00 0 38 0 1
#> 11.1 24.00 0 42 0 1
#> 185 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 34 24.00 0 36 0 0
#> 35 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 200 24.00 0 64 0 0
#> 74 24.00 0 43 0 1
#> 87 24.00 0 27 0 0
#> 82 24.00 0 34 0 0
#> 53 24.00 0 32 0 1
#> 98.1 24.00 0 34 1 0
#> 103 24.00 0 56 1 0
#> 21 24.00 0 47 0 0
#> 185.1 24.00 0 44 1 0
#> 35.1 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 146 24.00 0 63 1 0
#> 172 24.00 0 41 0 0
#> 186 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 160 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 160.1 24.00 0 31 1 0
#> 34.1 24.00 0 36 0 0
#> 146.1 24.00 0 63 1 0
#> 144 24.00 0 28 0 1
#> 186.1 24.00 0 45 1 0
#> 186.2 24.00 0 45 1 0
#> 120 24.00 0 68 0 1
#> 196 24.00 0 19 0 0
#> 19 24.00 0 57 0 1
#> 20 24.00 0 46 1 0
#> 163.1 24.00 0 66 0 0
#> 83 24.00 0 6 0 0
#> 135.1 24.00 0 58 1 0
#> 20.1 24.00 0 46 1 0
#> 72 24.00 0 40 0 1
#> 116 24.00 0 58 0 1
#> 17 24.00 0 38 0 1
#> 103.1 24.00 0 56 1 0
#> 44.1 24.00 0 56 0 0
#> 156.1 24.00 0 50 1 0
#> 173 24.00 0 19 0 1
#> 182 24.00 0 35 0 0
#> 160.2 24.00 0 31 1 0
#> 146.2 24.00 0 63 1 0
#> 120.1 24.00 0 68 0 1
#> 17.1 24.00 0 38 0 1
#> 138 24.00 0 44 1 0
#> 144.1 24.00 0 28 0 1
#> 131 24.00 0 66 0 0
#> 21.1 24.00 0 47 0 0
#> 74.1 24.00 0 43 0 1
#> 74.2 24.00 0 43 0 1
#> 137 24.00 0 45 1 0
#> 109 24.00 0 48 0 0
#> 80 24.00 0 41 0 0
#> 19.1 24.00 0 57 0 1
#> 71.1 24.00 0 51 0 0
#> 75 24.00 0 21 1 0
#> 185.2 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 173.1 24.00 0 19 0 1
#> 83.1 24.00 0 6 0 0
#> 147.1 24.00 0 76 1 0
#> 7 24.00 0 37 1 0
#> 162 24.00 0 51 0 0
#> 44.2 24.00 0 56 0 0
#> 178 24.00 0 52 1 0
#> 174 24.00 0 49 1 0
#> 174.1 24.00 0 49 1 0
#> 1 24.00 0 23 1 0
#> 126 24.00 0 48 0 0
#> 115 24.00 0 NA 1 0
#> 71.2 24.00 0 51 0 0
#> 193 24.00 0 45 0 1
#> 98.2 24.00 0 34 1 0
#> 83.2 24.00 0 6 0 0
#> 21.2 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.945 NA NA NA
#> 2 age, Cure model 0.0248 NA NA NA
#> 3 grade_ii, Cure model -0.331 NA NA NA
#> 4 grade_iii, Cure model 0.239 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00445 NA NA NA
#> 2 grade_ii, Survival model 0.562 NA NA NA
#> 3 grade_iii, Survival model 0.323 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.94488 0.02478 -0.33125 0.23895
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 254.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.94488472 0.02478228 -0.33124764 0.23894866
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004447462 0.562281139 0.323225383
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.126287025 0.982322273 0.698271541 0.200474139 0.400054105 0.380442166
#> [7] 0.613021629 0.919706322 0.380442166 0.901634443 0.361001168 0.613021629
#> [13] 0.819324240 0.004905594 0.726200660 0.537781869 0.518206737 0.439888677
#> [19] 0.159785233 0.782189018 0.266240468 0.537781869 0.488666344 0.865429537
#> [25] 0.946766754 0.670320927 0.064746167 0.782189018 0.038111011 0.095474536
#> [31] 0.200474139 0.200474139 0.275780803 0.016030617 0.159785233 0.937783425
#> [37] 0.528006182 0.810080379 0.051625351 0.148634630 0.973435473 0.865429537
#> [43] 0.800772224 0.537781869 0.200474139 0.744821735 0.256609556 0.439888677
#> [49] 0.584416690 0.847053794 0.892520242 0.901634443 0.670320927 0.095474536
#> [55] 0.819324240 0.351099463 0.982322273 0.537781869 0.865429537 0.321733653
#> [61] 0.275780803 0.410016105 0.603474188 0.237291055 0.837804799 0.763546162
#> [67] 0.964546600 0.772861451 0.928759011 0.651260963 0.537781869 0.064746167
#> [73] 0.716883517 0.698271541 0.410016105 0.726200660 0.429878056 0.478740394
#> [79] 0.095474536 0.084614007 0.016030617 0.641705099 0.439888677 0.321733653
#> [85] 0.632105995 0.275780803 0.584416690 0.275780803 0.946766754 0.247042495
#> [91] 0.847053794 0.137365202 0.180501591 0.180501591 0.754175793 0.651260963
#> [97] 0.361001168 0.670320927 0.341242043 0.275780803 0.439888677 0.508379183
#> [103] 0.498507610 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 194 127 29 99 8 179 100 145 179.1 61 76 100.1 56
#> 22.40 3.53 15.45 21.19 18.43 18.63 16.07 10.07 18.63 10.12 19.22 16.07 12.21
#> 24 133 85 171 51 197 14 158 192 134 107 183 167
#> 23.89 14.65 16.44 16.57 18.23 21.60 12.89 20.14 16.44 17.81 11.18 9.24 15.55
#> 63 14.1 164 169 99.1 99.2 166 168 197.1 187 181 154 92
#> 22.77 12.89 23.60 22.41 21.19 21.19 19.98 23.72 21.60 9.92 16.46 12.63 22.92
#> 136 77 107.1 140 85.1 99.3 57 68 51.1 5 43 93 61.1
#> 21.83 7.27 11.18 12.68 16.44 21.19 14.46 20.62 18.23 16.43 12.10 10.33 10.12
#> 167.1 169.1 56.1 58 127.1 85.2 107.2 105 166.1 88 79 90 49
#> 15.55 22.41 12.21 19.34 3.53 16.44 11.18 19.75 19.98 18.37 16.23 20.94 12.19
#> 60 149 155 101 6 192.1 63.1 18 29.1 88.1 133.1 108 41
#> 13.15 8.37 13.08 9.97 15.64 16.44 22.77 15.21 15.45 18.37 14.65 18.29 18.02
#> 169.2 15 168.1 125 51.2 105.1 26 166.2 5.1 166.3 183.1 32 43.1
#> 22.41 22.68 23.72 15.65 18.23 19.75 15.77 19.98 16.43 19.98 9.24 20.90 12.10
#> 66 139 139.1 81 6.1 76.1 167.2 170 166.4 51.3 117 184 135
#> 22.13 21.49 21.49 14.06 15.64 19.22 15.55 19.54 19.98 18.23 17.46 17.77 24.00
#> 11 98 44 47 11.1 185 71 132 34 35 152 200 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 82 53 98.1 103 21 185.1 35.1 142 146 172 186 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 160 38 156 160.1 34.1 146.1 144 186.1 186.2 120 196 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 163.1 83 135.1 20.1 72 116 17 103.1 44.1 156.1 173 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.2 146.2 120.1 17.1 138 144.1 131 21.1 74.1 74.2 137 109 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.1 71.1 75 185.2 64 173.1 83.1 147.1 7 162 44.2 178 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174.1 1 126 71.2 193 98.2 83.2 21.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[18]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005619246 0.470396560 0.318738942
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.671866964 0.009996429 0.390485801
#> grade_iii, Cure model
#> 0.901759679
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 168 23.72 1 70 0 0
#> 105 19.75 1 60 0 0
#> 128 20.35 1 35 0 1
#> 81 14.06 1 34 0 0
#> 124 9.73 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 56 12.21 1 60 0 0
#> 123 13.00 1 44 1 0
#> 140 12.68 1 59 1 0
#> 123.1 13.00 1 44 1 0
#> 79 16.23 1 54 1 0
#> 140.1 12.68 1 59 1 0
#> 56.1 12.21 1 60 0 0
#> 184 17.77 1 38 0 0
#> 26 15.77 1 49 0 1
#> 10 10.53 1 34 0 0
#> 101 9.97 1 10 0 1
#> 45 17.42 1 54 0 1
#> 171 16.57 1 41 0 1
#> 79.1 16.23 1 54 1 0
#> 45.1 17.42 1 54 0 1
#> 60 13.15 1 38 1 0
#> 183 9.24 1 67 1 0
#> 16 8.71 1 71 0 1
#> 164 23.60 1 76 0 1
#> 18 15.21 1 49 1 0
#> 168.1 23.72 1 70 0 0
#> 78 23.88 1 43 0 0
#> 14 12.89 1 21 0 0
#> 52 10.42 1 52 0 1
#> 158 20.14 1 74 1 0
#> 157 15.10 1 47 0 0
#> 123.2 13.00 1 44 1 0
#> 107 11.18 1 54 1 0
#> 133 14.65 1 57 0 0
#> 187 9.92 1 39 1 0
#> 91 5.33 1 61 0 1
#> 16.1 8.71 1 71 0 1
#> 159 10.55 1 50 0 1
#> 106 16.67 1 49 1 0
#> 42 12.43 1 49 0 1
#> 125 15.65 1 67 1 0
#> 187.1 9.92 1 39 1 0
#> 40 18.00 1 28 1 0
#> 43 12.10 1 61 0 1
#> 192 16.44 1 31 1 0
#> 8 18.43 1 32 0 0
#> 153 21.33 1 55 1 0
#> 50 10.02 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 36 21.19 1 48 0 1
#> 88 18.37 1 47 0 0
#> 43.1 12.10 1 61 0 1
#> 51 18.23 1 83 0 1
#> 166 19.98 1 48 0 0
#> 5 16.43 1 51 0 1
#> 57 14.46 1 45 0 1
#> 195 11.76 1 NA 1 0
#> 125.1 15.65 1 67 1 0
#> 106.1 16.67 1 49 1 0
#> 155 13.08 1 26 0 0
#> 91.1 5.33 1 61 0 1
#> 166.1 19.98 1 48 0 0
#> 108 18.29 1 39 0 1
#> 81.1 14.06 1 34 0 0
#> 184.1 17.77 1 38 0 0
#> 105.1 19.75 1 60 0 0
#> 184.2 17.77 1 38 0 0
#> 108.1 18.29 1 39 0 1
#> 68 20.62 1 44 0 0
#> 184.3 17.77 1 38 0 0
#> 90 20.94 1 50 0 1
#> 77 7.27 1 67 0 1
#> 105.2 19.75 1 60 0 0
#> 40.1 18.00 1 28 1 0
#> 101.1 9.97 1 10 0 1
#> 41 18.02 1 40 1 0
#> 36.1 21.19 1 48 0 1
#> 85 16.44 1 36 0 0
#> 77.1 7.27 1 67 0 1
#> 79.2 16.23 1 54 1 0
#> 101.2 9.97 1 10 0 1
#> 79.3 16.23 1 54 1 0
#> 69 23.23 1 25 0 1
#> 81.2 14.06 1 34 0 0
#> 128.1 20.35 1 35 0 1
#> 32 20.90 1 37 1 0
#> 30 17.43 1 78 0 0
#> 93 10.33 1 52 0 1
#> 97 19.14 1 65 0 1
#> 43.2 12.10 1 61 0 1
#> 63 22.77 1 31 1 0
#> 86 23.81 1 58 0 1
#> 25 6.32 1 34 1 0
#> 37 12.52 1 57 1 0
#> 18.1 15.21 1 49 1 0
#> 76 19.22 1 54 0 1
#> 181 16.46 1 45 0 1
#> 139 21.49 1 63 1 0
#> 155.1 13.08 1 26 0 0
#> 25.1 6.32 1 34 1 0
#> 177 12.53 1 75 0 0
#> 29 15.45 1 68 1 0
#> 134 17.81 1 47 1 0
#> 26.1 15.77 1 49 0 1
#> 154 12.63 1 20 1 0
#> 171.1 16.57 1 41 0 1
#> 150 20.33 1 48 0 0
#> 91.2 5.33 1 61 0 1
#> 43.3 12.10 1 61 0 1
#> 50.1 10.02 1 NA 1 0
#> 51.1 18.23 1 83 0 1
#> 67 24.00 0 25 0 0
#> 121 24.00 0 57 1 0
#> 31 24.00 0 36 0 1
#> 142 24.00 0 53 0 0
#> 1 24.00 0 23 1 0
#> 196 24.00 0 19 0 0
#> 163 24.00 0 66 0 0
#> 176 24.00 0 43 0 1
#> 141 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 156 24.00 0 50 1 0
#> 95 24.00 0 68 0 1
#> 146 24.00 0 63 1 0
#> 104 24.00 0 50 1 0
#> 112 24.00 0 61 0 0
#> 173 24.00 0 19 0 1
#> 65 24.00 0 57 1 0
#> 141.1 24.00 0 44 1 0
#> 172 24.00 0 41 0 0
#> 21 24.00 0 47 0 0
#> 22 24.00 0 52 1 0
#> 71 24.00 0 51 0 0
#> 21.1 24.00 0 47 0 0
#> 109 24.00 0 48 0 0
#> 163.1 24.00 0 66 0 0
#> 64 24.00 0 43 0 0
#> 198 24.00 0 66 0 1
#> 138 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 35 24.00 0 51 0 0
#> 35.1 24.00 0 51 0 0
#> 122.1 24.00 0 66 0 0
#> 95.1 24.00 0 68 0 1
#> 31.1 24.00 0 36 0 1
#> 12 24.00 0 63 0 0
#> 185 24.00 0 44 1 0
#> 193 24.00 0 45 0 1
#> 147 24.00 0 76 1 0
#> 74 24.00 0 43 0 1
#> 116 24.00 0 58 0 1
#> 9 24.00 0 31 1 0
#> 138.1 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 147.1 24.00 0 76 1 0
#> 102 24.00 0 49 0 0
#> 173.1 24.00 0 19 0 1
#> 131 24.00 0 66 0 0
#> 152 24.00 0 36 0 1
#> 38.1 24.00 0 31 1 0
#> 141.2 24.00 0 44 1 0
#> 21.2 24.00 0 47 0 0
#> 48 24.00 0 31 1 0
#> 176.1 24.00 0 43 0 1
#> 146.1 24.00 0 63 1 0
#> 12.1 24.00 0 63 0 0
#> 84 24.00 0 39 0 1
#> 21.3 24.00 0 47 0 0
#> 21.4 24.00 0 47 0 0
#> 104.1 24.00 0 50 1 0
#> 46 24.00 0 71 0 0
#> 120 24.00 0 68 0 1
#> 172.1 24.00 0 41 0 0
#> 83 24.00 0 6 0 0
#> 102.1 24.00 0 49 0 0
#> 17 24.00 0 38 0 1
#> 62 24.00 0 71 0 0
#> 115 24.00 0 NA 1 0
#> 3 24.00 0 31 1 0
#> 1.1 24.00 0 23 1 0
#> 196.1 24.00 0 19 0 0
#> 53 24.00 0 32 0 1
#> 11 24.00 0 42 0 1
#> 71.1 24.00 0 51 0 0
#> 185.1 24.00 0 44 1 0
#> 83.1 24.00 0 6 0 0
#> 2 24.00 0 9 0 0
#> 131.1 24.00 0 66 0 0
#> 35.2 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 196.2 24.00 0 19 0 0
#> 20 24.00 0 46 1 0
#> 95.2 24.00 0 68 0 1
#> 62.1 24.00 0 71 0 0
#> 152.1 24.00 0 36 0 1
#> 64.1 24.00 0 43 0 0
#> 103 24.00 0 56 1 0
#> 196.3 24.00 0 19 0 0
#> 135 24.00 0 58 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.672 NA NA NA
#> 2 age, Cure model 0.0100 NA NA NA
#> 3 grade_ii, Cure model 0.390 NA NA NA
#> 4 grade_iii, Cure model 0.902 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00562 NA NA NA
#> 2 grade_ii, Survival model 0.470 NA NA NA
#> 3 grade_iii, Survival model 0.319 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.671867 0.009996 0.390486 0.901760
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 259.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.671866964 0.009996429 0.390485801 0.901759679
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005619246 0.470396560 0.318738942
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.020357260 0.188189823 0.134288306 0.614048054 0.235250557 0.762132038
#> [7] 0.669894043 0.706730931 0.669894043 0.484504887 0.706730931 0.762132038
#> [13] 0.341825600 0.521134870 0.835789503 0.863683428 0.388929545 0.427350822
#> [19] 0.484504887 0.388929545 0.641856671 0.909212245 0.918351247 0.038585153
#> [25] 0.567652353 0.020357260 0.003247061 0.697418779 0.845090219 0.160905946
#> [31] 0.586053437 0.669894043 0.817219990 0.595361546 0.891008181 0.972924171
#> [37] 0.918351247 0.826506754 0.408237430 0.752892296 0.539754054 0.891008181
#> [43] 0.313391371 0.780627088 0.455992778 0.245014168 0.079460289 0.088950459
#> [49] 0.254842278 0.780627088 0.284073602 0.170013398 0.474940761 0.604709713
#> [55] 0.539754054 0.408237430 0.651223197 0.972924171 0.170013398 0.264759195
#> [61] 0.614048054 0.341825600 0.188189823 0.341825600 0.264759195 0.125083856
#> [67] 0.341825600 0.106750585 0.936566123 0.188189823 0.313391371 0.863683428
#> [73] 0.303570427 0.088950459 0.455992778 0.936566123 0.484504887 0.863683428
#> [79] 0.484504887 0.049467069 0.614048054 0.134288306 0.116025648 0.379145237
#> [85] 0.854388183 0.225571441 0.780627088 0.059911511 0.011600755 0.954800910
#> [91] 0.743647524 0.567652353 0.215911224 0.446385730 0.069769133 0.651223197
#> [97] 0.954800910 0.734384104 0.558310284 0.332297235 0.521134870 0.725160695
#> [103] 0.427350822 0.151769635 0.972924171 0.780627088 0.284073602 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000
#>
#> $Time
#> 168 105 128 81 179 56 123 140 123.1 79 140.1 56.1 184
#> 23.72 19.75 20.35 14.06 18.63 12.21 13.00 12.68 13.00 16.23 12.68 12.21 17.77
#> 26 10 101 45 171 79.1 45.1 60 183 16 164 18 168.1
#> 15.77 10.53 9.97 17.42 16.57 16.23 17.42 13.15 9.24 8.71 23.60 15.21 23.72
#> 78 14 52 158 157 123.2 107 133 187 91 16.1 159 106
#> 23.88 12.89 10.42 20.14 15.10 13.00 11.18 14.65 9.92 5.33 8.71 10.55 16.67
#> 42 125 187.1 40 43 192 8 153 36 88 43.1 51 166
#> 12.43 15.65 9.92 18.00 12.10 16.44 18.43 21.33 21.19 18.37 12.10 18.23 19.98
#> 5 57 125.1 106.1 155 91.1 166.1 108 81.1 184.1 105.1 184.2 108.1
#> 16.43 14.46 15.65 16.67 13.08 5.33 19.98 18.29 14.06 17.77 19.75 17.77 18.29
#> 68 184.3 90 77 105.2 40.1 101.1 41 36.1 85 77.1 79.2 101.2
#> 20.62 17.77 20.94 7.27 19.75 18.00 9.97 18.02 21.19 16.44 7.27 16.23 9.97
#> 79.3 69 81.2 128.1 32 30 93 97 43.2 63 86 25 37
#> 16.23 23.23 14.06 20.35 20.90 17.43 10.33 19.14 12.10 22.77 23.81 6.32 12.52
#> 18.1 76 181 139 155.1 25.1 177 29 134 26.1 154 171.1 150
#> 15.21 19.22 16.46 21.49 13.08 6.32 12.53 15.45 17.81 15.77 12.63 16.57 20.33
#> 91.2 43.3 51.1 67 121 31 142 1 196 163 176 141 7
#> 5.33 12.10 18.23 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 95 146 104 112 173 65 141.1 172 21 22 71 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 163.1 64 198 138 122 35 35.1 122.1 95.1 31.1 12 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 147 74 116 9 138.1 38 147.1 102 173.1 131 152 38.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.2 21.2 48 176.1 146.1 12.1 84 21.3 21.4 104.1 46 120 172.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 102.1 17 62 3 1.1 196.1 53 11 71.1 185.1 83.1 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 35.2 160 196.2 20 95.2 62.1 152.1 64.1 103 196.3 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[19]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005884943 0.441058272 0.151723896
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.93101959 0.01345049 0.70813912
#> grade_iii, Cure model
#> 1.04658175
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 175 21.91 1 43 0 0
#> 61 10.12 1 36 0 1
#> 56 12.21 1 60 0 0
#> 42 12.43 1 49 0 1
#> 96 14.54 1 33 0 1
#> 41 18.02 1 40 1 0
#> 69 23.23 1 25 0 1
#> 134 17.81 1 47 1 0
#> 166 19.98 1 48 0 0
#> 183 9.24 1 67 1 0
#> 23 16.92 1 61 0 0
#> 97 19.14 1 65 0 1
#> 18 15.21 1 49 1 0
#> 155 13.08 1 26 0 0
#> 37 12.52 1 57 1 0
#> 37.1 12.52 1 57 1 0
#> 68 20.62 1 44 0 0
#> 145 10.07 1 65 1 0
#> 43 12.10 1 61 0 1
#> 63 22.77 1 31 1 0
#> 14 12.89 1 21 0 0
#> 124 9.73 1 NA 1 0
#> 10 10.53 1 34 0 0
#> 159 10.55 1 50 0 1
#> 88 18.37 1 47 0 0
#> 37.2 12.52 1 57 1 0
#> 41.1 18.02 1 40 1 0
#> 171 16.57 1 41 0 1
#> 99 21.19 1 38 0 1
#> 89 11.44 1 NA 0 0
#> 79 16.23 1 54 1 0
#> 57 14.46 1 45 0 1
#> 197 21.60 1 69 1 0
#> 41.2 18.02 1 40 1 0
#> 49 12.19 1 48 1 0
#> 43.1 12.10 1 61 0 1
#> 6 15.64 1 39 0 0
#> 129 23.41 1 53 1 0
#> 92 22.92 1 47 0 1
#> 24 23.89 1 38 0 0
#> 59 10.16 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 63.1 22.77 1 31 1 0
#> 188 16.16 1 46 0 1
#> 167 15.55 1 56 1 0
#> 171.1 16.57 1 41 0 1
#> 166.1 19.98 1 48 0 0
#> 77 7.27 1 67 0 1
#> 25 6.32 1 34 1 0
#> 56.1 12.21 1 60 0 0
#> 164 23.60 1 76 0 1
#> 168 23.72 1 70 0 0
#> 8 18.43 1 32 0 0
#> 128 20.35 1 35 0 1
#> 190 20.81 1 42 1 0
#> 154 12.63 1 20 1 0
#> 170 19.54 1 43 0 1
#> 189 10.51 1 NA 1 0
#> 85 16.44 1 36 0 0
#> 154.1 12.63 1 20 1 0
#> 107 11.18 1 54 1 0
#> 89.1 11.44 1 NA 0 0
#> 92.1 22.92 1 47 0 1
#> 177 12.53 1 75 0 0
#> 188.1 16.16 1 46 0 1
#> 134.1 17.81 1 47 1 0
#> 78.1 23.88 1 43 0 0
#> 6.1 15.64 1 39 0 0
#> 195 11.76 1 NA 1 0
#> 134.2 17.81 1 47 1 0
#> 36 21.19 1 48 0 1
#> 41.3 18.02 1 40 1 0
#> 91 5.33 1 61 0 1
#> 179 18.63 1 42 0 0
#> 129.1 23.41 1 53 1 0
#> 59.1 10.16 1 NA 1 0
#> 99.1 21.19 1 38 0 1
#> 43.2 12.10 1 61 0 1
#> 51 18.23 1 83 0 1
#> 23.1 16.92 1 61 0 0
#> 60 13.15 1 38 1 0
#> 194 22.40 1 38 0 1
#> 49.1 12.19 1 48 1 0
#> 133 14.65 1 57 0 0
#> 125 15.65 1 67 1 0
#> 36.1 21.19 1 48 0 1
#> 169 22.41 1 46 0 0
#> 4 17.64 1 NA 0 1
#> 166.2 19.98 1 48 0 0
#> 130 16.47 1 53 0 1
#> 100 16.07 1 60 0 0
#> 92.2 22.92 1 47 0 1
#> 113 22.86 1 34 0 0
#> 139 21.49 1 63 1 0
#> 97.1 19.14 1 65 0 1
#> 89.2 11.44 1 NA 0 0
#> 157 15.10 1 47 0 0
#> 166.3 19.98 1 48 0 0
#> 155.1 13.08 1 26 0 0
#> 58 19.34 1 39 0 0
#> 194.1 22.40 1 38 0 1
#> 110 17.56 1 65 0 1
#> 150 20.33 1 48 0 0
#> 51.1 18.23 1 83 0 1
#> 76 19.22 1 54 0 1
#> 49.2 12.19 1 48 1 0
#> 63.2 22.77 1 31 1 0
#> 66 22.13 1 53 0 0
#> 36.2 21.19 1 48 0 1
#> 180 14.82 1 37 0 0
#> 41.4 18.02 1 40 1 0
#> 149 8.37 1 33 1 0
#> 185 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 141 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 196 24.00 0 19 0 0
#> 143 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 198.1 24.00 0 66 0 1
#> 132 24.00 0 55 0 0
#> 200 24.00 0 64 0 0
#> 17.1 24.00 0 38 0 1
#> 116 24.00 0 58 0 1
#> 34 24.00 0 36 0 0
#> 11.1 24.00 0 42 0 1
#> 162 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#> 178 24.00 0 52 1 0
#> 122 24.00 0 66 0 0
#> 82 24.00 0 34 0 0
#> 160 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 67 24.00 0 25 0 0
#> 28 24.00 0 67 1 0
#> 84 24.00 0 39 0 1
#> 176 24.00 0 43 0 1
#> 135 24.00 0 58 1 0
#> 173 24.00 0 19 0 1
#> 112 24.00 0 61 0 0
#> 120 24.00 0 68 0 1
#> 19 24.00 0 57 0 1
#> 119 24.00 0 17 0 0
#> 102.1 24.00 0 49 0 0
#> 44 24.00 0 56 0 0
#> 75 24.00 0 21 1 0
#> 104 24.00 0 50 1 0
#> 147 24.00 0 76 1 0
#> 102.2 24.00 0 49 0 0
#> 112.1 24.00 0 61 0 0
#> 119.1 24.00 0 17 0 0
#> 165 24.00 0 47 0 0
#> 109 24.00 0 48 0 0
#> 178.1 24.00 0 52 1 0
#> 144 24.00 0 28 0 1
#> 2 24.00 0 9 0 0
#> 28.1 24.00 0 67 1 0
#> 109.1 24.00 0 48 0 0
#> 12 24.00 0 63 0 0
#> 46 24.00 0 71 0 0
#> 2.1 24.00 0 9 0 0
#> 131 24.00 0 66 0 0
#> 200.1 24.00 0 64 0 0
#> 67.1 24.00 0 25 0 0
#> 141.1 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 119.2 24.00 0 17 0 0
#> 120.1 24.00 0 68 0 1
#> 2.2 24.00 0 9 0 0
#> 1 24.00 0 23 1 0
#> 162.1 24.00 0 51 0 0
#> 2.3 24.00 0 9 0 0
#> 74 24.00 0 43 0 1
#> 33.1 24.00 0 53 0 0
#> 138 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 87 24.00 0 27 0 0
#> 28.2 24.00 0 67 1 0
#> 98 24.00 0 34 1 0
#> 2.4 24.00 0 9 0 0
#> 135.1 24.00 0 58 1 0
#> 116.1 24.00 0 58 0 1
#> 161.1 24.00 0 45 0 0
#> 44.1 24.00 0 56 0 0
#> 146 24.00 0 63 1 0
#> 131.1 24.00 0 66 0 0
#> 2.5 24.00 0 9 0 0
#> 75.1 24.00 0 21 1 0
#> 1.1 24.00 0 23 1 0
#> 64 24.00 0 43 0 0
#> 119.3 24.00 0 17 0 0
#> 7 24.00 0 37 1 0
#> 1.2 24.00 0 23 1 0
#> 115 24.00 0 NA 1 0
#> 64.1 24.00 0 43 0 0
#> 151.1 24.00 0 42 0 0
#> 71 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 132.1 24.00 0 55 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.931 NA NA NA
#> 2 age, Cure model 0.0135 NA NA NA
#> 3 grade_ii, Cure model 0.708 NA NA NA
#> 4 grade_iii, Cure model 1.05 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00588 NA NA NA
#> 2 grade_ii, Survival model 0.441 NA NA NA
#> 3 grade_iii, Survival model 0.152 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.93102 0.01345 0.70814 1.04658
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 249.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.93101959 0.01345049 0.70813912 1.04658175
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005884943 0.441058272 0.151723896
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.35772280 0.95817000 0.88986943 0.88341290 0.80333096 0.60384784
#> [7] 0.20179816 0.64293037 0.47849748 0.97031052 0.67343303 0.54256314
#> [13] 0.77559508 0.82385487 0.86410711 0.86410711 0.44940745 0.96426469
#> [19] 0.92135089 0.27379459 0.83735304 0.95205827 0.94593783 0.57800234
#> [25] 0.86410711 0.60384784 0.68849036 0.39149975 0.71825920 0.81021022
#> [31] 0.36943155 0.60384784 0.90265735 0.92135089 0.75442019 0.16933461
#> [37] 0.21826085 0.03253981 0.07239064 0.27379459 0.72559804 0.76856519
#> [43] 0.68849036 0.47849748 0.98227208 0.98821042 0.88986943 0.14725179
#> [49] 0.12208858 0.56914832 0.45918490 0.43956674 0.84412234 0.51492083
#> [55] 0.71083418 0.84412234 0.93979506 0.21826085 0.85744734 0.72559804
#> [61] 0.64293037 0.07239064 0.75442019 0.64293037 0.39149975 0.60384784
#> [67] 0.99411686 0.56026567 0.16933461 0.39149975 0.92135089 0.58681335
#> [73] 0.67343303 0.81705943 0.32237735 0.90265735 0.79642727 0.74727952
#> [79] 0.39149975 0.30997219 0.47849748 0.70339082 0.74004864 0.21826085
#> [85] 0.25944581 0.38066578 0.54256314 0.78255720 0.47849748 0.82385487
#> [91] 0.52419460 0.32237735 0.66578757 0.46887364 0.58681335 0.53342624
#> [97] 0.90265735 0.27379459 0.34590269 0.39149975 0.78949965 0.60384784
#> [103] 0.97630756 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 175 61 56 42 96 41 69 134 166 183 23 97 18
#> 21.91 10.12 12.21 12.43 14.54 18.02 23.23 17.81 19.98 9.24 16.92 19.14 15.21
#> 155 37 37.1 68 145 43 63 14 10 159 88 37.2 41.1
#> 13.08 12.52 12.52 20.62 10.07 12.10 22.77 12.89 10.53 10.55 18.37 12.52 18.02
#> 171 99 79 57 197 41.2 49 43.1 6 129 92 24 78
#> 16.57 21.19 16.23 14.46 21.60 18.02 12.19 12.10 15.64 23.41 22.92 23.89 23.88
#> 63.1 188 167 171.1 166.1 77 25 56.1 164 168 8 128 190
#> 22.77 16.16 15.55 16.57 19.98 7.27 6.32 12.21 23.60 23.72 18.43 20.35 20.81
#> 154 170 85 154.1 107 92.1 177 188.1 134.1 78.1 6.1 134.2 36
#> 12.63 19.54 16.44 12.63 11.18 22.92 12.53 16.16 17.81 23.88 15.64 17.81 21.19
#> 41.3 91 179 129.1 99.1 43.2 51 23.1 60 194 49.1 133 125
#> 18.02 5.33 18.63 23.41 21.19 12.10 18.23 16.92 13.15 22.40 12.19 14.65 15.65
#> 36.1 169 166.2 130 100 92.2 113 139 97.1 157 166.3 155.1 58
#> 21.19 22.41 19.98 16.47 16.07 22.92 22.86 21.49 19.14 15.10 19.98 13.08 19.34
#> 194.1 110 150 51.1 76 49.2 63.2 66 36.2 180 41.4 149 185
#> 22.40 17.56 20.33 18.23 19.22 12.19 22.77 22.13 21.19 14.82 18.02 8.37 24.00
#> 17 141 198 196 143 11 198.1 132 200 17.1 116 34 11.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 102 178 122 82 160 33 67 28 84 176 135 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 120 19 119 102.1 44 75 104 147 102.2 112.1 119.1 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 178.1 144 2 28.1 109.1 12 46 2.1 131 200.1 67.1 141.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 119.2 120.1 2.2 1 162.1 2.3 74 33.1 138 161 87 28.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 2.4 135.1 116.1 161.1 44.1 146 131.1 2.5 75.1 1.1 64 119.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 1.2 64.1 151.1 71 48 172 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[20]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001267178 0.203575529 0.219974418
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.140712057 0.001008072 -0.003533644
#> grade_iii, Cure model
#> 0.761797462
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 189 10.51 1 NA 1 0
#> 171 16.57 1 41 0 1
#> 5 16.43 1 51 0 1
#> 30 17.43 1 78 0 0
#> 78 23.88 1 43 0 0
#> 129 23.41 1 53 1 0
#> 26 15.77 1 49 0 1
#> 49 12.19 1 48 1 0
#> 26.1 15.77 1 49 0 1
#> 117 17.46 1 26 0 1
#> 101 9.97 1 10 0 1
#> 167 15.55 1 56 1 0
#> 6 15.64 1 39 0 0
#> 88 18.37 1 47 0 0
#> 18 15.21 1 49 1 0
#> 136 21.83 1 43 0 1
#> 36 21.19 1 48 0 1
#> 128 20.35 1 35 0 1
#> 158 20.14 1 74 1 0
#> 61 10.12 1 36 0 1
#> 6.1 15.64 1 39 0 0
#> 15 22.68 1 48 0 0
#> 125 15.65 1 67 1 0
#> 180 14.82 1 37 0 0
#> 60 13.15 1 38 1 0
#> 199 19.81 1 NA 0 1
#> 88.1 18.37 1 47 0 0
#> 107 11.18 1 54 1 0
#> 180.1 14.82 1 37 0 0
#> 199.1 19.81 1 NA 0 1
#> 16 8.71 1 71 0 1
#> 39 15.59 1 37 0 1
#> 139 21.49 1 63 1 0
#> 68 20.62 1 44 0 0
#> 55 19.34 1 69 0 1
#> 24 23.89 1 38 0 0
#> 16.1 8.71 1 71 0 1
#> 32 20.90 1 37 1 0
#> 157 15.10 1 47 0 0
#> 134 17.81 1 47 1 0
#> 100 16.07 1 60 0 0
#> 125.1 15.65 1 67 1 0
#> 127 3.53 1 62 0 1
#> 59 10.16 1 NA 1 0
#> 139.1 21.49 1 63 1 0
#> 39.1 15.59 1 37 0 1
#> 181 16.46 1 45 0 1
#> 59.1 10.16 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 8 18.43 1 32 0 0
#> 99 21.19 1 38 0 1
#> 107.1 11.18 1 54 1 0
#> 69 23.23 1 25 0 1
#> 190 20.81 1 42 1 0
#> 52 10.42 1 52 0 1
#> 32.1 20.90 1 37 1 0
#> 164 23.60 1 76 0 1
#> 177 12.53 1 75 0 0
#> 14 12.89 1 21 0 0
#> 92.1 22.92 1 47 0 1
#> 13 14.34 1 54 0 1
#> 43 12.10 1 61 0 1
#> 190.1 20.81 1 42 1 0
#> 32.2 20.90 1 37 1 0
#> 192 16.44 1 31 1 0
#> 134.1 17.81 1 47 1 0
#> 145 10.07 1 65 1 0
#> 124 9.73 1 NA 1 0
#> 43.1 12.10 1 61 0 1
#> 150 20.33 1 48 0 0
#> 189.1 10.51 1 NA 1 0
#> 43.2 12.10 1 61 0 1
#> 171.1 16.57 1 41 0 1
#> 166 19.98 1 48 0 0
#> 63 22.77 1 31 1 0
#> 171.2 16.57 1 41 0 1
#> 61.1 10.12 1 36 0 1
#> 113 22.86 1 34 0 0
#> 10 10.53 1 34 0 0
#> 57 14.46 1 45 0 1
#> 86 23.81 1 58 0 1
#> 136.1 21.83 1 43 0 1
#> 45 17.42 1 54 0 1
#> 13.1 14.34 1 54 0 1
#> 99.1 21.19 1 38 0 1
#> 171.3 16.57 1 41 0 1
#> 14.1 12.89 1 21 0 0
#> 10.1 10.53 1 34 0 0
#> 76 19.22 1 54 0 1
#> 61.2 10.12 1 36 0 1
#> 18.1 15.21 1 49 1 0
#> 105 19.75 1 60 0 0
#> 43.3 12.10 1 61 0 1
#> 190.2 20.81 1 42 1 0
#> 43.4 12.10 1 61 0 1
#> 168 23.72 1 70 0 0
#> 124.1 9.73 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 29 15.45 1 68 1 0
#> 56 12.21 1 60 0 0
#> 128.1 20.35 1 35 0 1
#> 139.2 21.49 1 63 1 0
#> 166.1 19.98 1 48 0 0
#> 180.2 14.82 1 37 0 0
#> 4 17.64 1 NA 0 1
#> 10.2 10.53 1 34 0 0
#> 100.1 16.07 1 60 0 0
#> 111 17.45 1 47 0 1
#> 123 13.00 1 44 1 0
#> 15.1 22.68 1 48 0 0
#> 149 8.37 1 33 1 0
#> 183 9.24 1 67 1 0
#> 21 24.00 0 47 0 0
#> 72 24.00 0 40 0 1
#> 19 24.00 0 57 0 1
#> 67 24.00 0 25 0 0
#> 17 24.00 0 38 0 1
#> 152 24.00 0 36 0 1
#> 102 24.00 0 49 0 0
#> 82 24.00 0 34 0 0
#> 1 24.00 0 23 1 0
#> 138 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 152.1 24.00 0 36 0 1
#> 121 24.00 0 57 1 0
#> 104 24.00 0 50 1 0
#> 146 24.00 0 63 1 0
#> 48 24.00 0 31 1 0
#> 19.1 24.00 0 57 0 1
#> 64 24.00 0 43 0 0
#> 62 24.00 0 71 0 0
#> 160 24.00 0 31 1 0
#> 102.1 24.00 0 49 0 0
#> 148 24.00 0 61 1 0
#> 118 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 161 24.00 0 45 0 0
#> 65 24.00 0 57 1 0
#> 198.1 24.00 0 66 0 1
#> 109 24.00 0 48 0 0
#> 53 24.00 0 32 0 1
#> 200 24.00 0 64 0 0
#> 65.1 24.00 0 57 1 0
#> 196 24.00 0 19 0 0
#> 28 24.00 0 67 1 0
#> 185 24.00 0 44 1 0
#> 104.1 24.00 0 50 1 0
#> 148.1 24.00 0 61 1 0
#> 198.2 24.00 0 66 0 1
#> 135 24.00 0 58 1 0
#> 193 24.00 0 45 0 1
#> 143 24.00 0 51 0 0
#> 148.2 24.00 0 61 1 0
#> 152.2 24.00 0 36 0 1
#> 34 24.00 0 36 0 0
#> 137 24.00 0 45 1 0
#> 120 24.00 0 68 0 1
#> 34.1 24.00 0 36 0 0
#> 137.1 24.00 0 45 1 0
#> 12 24.00 0 63 0 0
#> 161.1 24.00 0 45 0 0
#> 191 24.00 0 60 0 1
#> 138.1 24.00 0 44 1 0
#> 196.1 24.00 0 19 0 0
#> 27 24.00 0 63 1 0
#> 67.1 24.00 0 25 0 0
#> 162 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 191.1 24.00 0 60 0 1
#> 122 24.00 0 66 0 0
#> 198.3 24.00 0 66 0 1
#> 118.1 24.00 0 44 1 0
#> 2 24.00 0 9 0 0
#> 116 24.00 0 58 0 1
#> 185.1 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 163 24.00 0 66 0 0
#> 94 24.00 0 51 0 1
#> 126 24.00 0 48 0 0
#> 83 24.00 0 6 0 0
#> 163.1 24.00 0 66 0 0
#> 62.1 24.00 0 71 0 0
#> 38 24.00 0 31 1 0
#> 146.1 24.00 0 63 1 0
#> 64.1 24.00 0 43 0 0
#> 98 24.00 0 34 1 0
#> 137.2 24.00 0 45 1 0
#> 75.1 24.00 0 21 1 0
#> 83.1 24.00 0 6 0 0
#> 138.2 24.00 0 44 1 0
#> 47 24.00 0 38 0 1
#> 31 24.00 0 36 0 1
#> 178 24.00 0 52 1 0
#> 126.1 24.00 0 48 0 0
#> 200.1 24.00 0 64 0 0
#> 163.2 24.00 0 66 0 0
#> 182 24.00 0 35 0 0
#> 65.2 24.00 0 57 1 0
#> 95 24.00 0 68 0 1
#> 104.2 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.141 NA NA NA
#> 2 age, Cure model 0.00101 NA NA NA
#> 3 grade_ii, Cure model -0.00353 NA NA NA
#> 4 grade_iii, Cure model 0.762 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00127 NA NA NA
#> 2 grade_ii, Survival model 0.204 NA NA NA
#> 3 grade_iii, Survival model 0.220 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.140712 0.001008 -0.003534 0.761797
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 257.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.140712057 0.001008072 -0.003533644 0.761797462
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001267178 0.203575529 0.219974418
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.53612691 0.58897133 0.51772519 0.03066048 0.09727993 0.61532512
#> [7] 0.82577063 0.61532512 0.49918102 0.95303763 0.68407695 0.64986990
#> [13] 0.45235501 0.70111802 0.19980583 0.25521866 0.35566089 0.38496271
#> [19] 0.92151853 0.64986990 0.17576033 0.63267633 0.72633102 0.77624127
#> [25] 0.45235501 0.87366452 0.72633102 0.96880787 0.66704048 0.22297502
#> [31] 0.34562625 0.42363509 0.01182229 0.96880787 0.28624188 0.71789767
#> [37] 0.48065720 0.59781305 0.63267633 0.99221104 0.22297502 0.66704048
#> [43] 0.57116251 0.12566121 0.44281102 0.25521866 0.87366452 0.11172679
#> [49] 0.31634065 0.91351884 0.28624188 0.08213972 0.80926062 0.79281165
#> [55] 0.12566121 0.75968330 0.83399746 0.31634065 0.28624188 0.58008571
#> [61] 0.48065720 0.94512452 0.83399746 0.37511987 0.83399746 0.53612691
#> [67] 0.39471918 0.16318660 0.53612691 0.92151853 0.15034144 0.88966078
#> [73] 0.75129727 0.04930173 0.19980583 0.52695290 0.75968330 0.25521866
#> [79] 0.53612691 0.79281165 0.88966078 0.43325851 0.92151853 0.70111802
#> [85] 0.41393235 0.83399746 0.31634065 0.83399746 0.06589856 0.47119349
#> [91] 0.69261510 0.81751892 0.35566089 0.22297502 0.39471918 0.72633102
#> [97] 0.88966078 0.59781305 0.50848036 0.78453941 0.17576033 0.98440075
#> [103] 0.96093357 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 171 5 30 78 129 26 49 26.1 117 101 167 6 88
#> 16.57 16.43 17.43 23.88 23.41 15.77 12.19 15.77 17.46 9.97 15.55 15.64 18.37
#> 18 136 36 128 158 61 6.1 15 125 180 60 88.1 107
#> 15.21 21.83 21.19 20.35 20.14 10.12 15.64 22.68 15.65 14.82 13.15 18.37 11.18
#> 180.1 16 39 139 68 55 24 16.1 32 157 134 100 125.1
#> 14.82 8.71 15.59 21.49 20.62 19.34 23.89 8.71 20.90 15.10 17.81 16.07 15.65
#> 127 139.1 39.1 181 92 8 99 107.1 69 190 52 32.1 164
#> 3.53 21.49 15.59 16.46 22.92 18.43 21.19 11.18 23.23 20.81 10.42 20.90 23.60
#> 177 14 92.1 13 43 190.1 32.2 192 134.1 145 43.1 150 43.2
#> 12.53 12.89 22.92 14.34 12.10 20.81 20.90 16.44 17.81 10.07 12.10 20.33 12.10
#> 171.1 166 63 171.2 61.1 113 10 57 86 136.1 45 13.1 99.1
#> 16.57 19.98 22.77 16.57 10.12 22.86 10.53 14.46 23.81 21.83 17.42 14.34 21.19
#> 171.3 14.1 10.1 76 61.2 18.1 105 43.3 190.2 43.4 168 40 29
#> 16.57 12.89 10.53 19.22 10.12 15.21 19.75 12.10 20.81 12.10 23.72 18.00 15.45
#> 56 128.1 139.2 166.1 180.2 10.2 100.1 111 123 15.1 149 183 21
#> 12.21 20.35 21.49 19.98 14.82 10.53 16.07 17.45 13.00 22.68 8.37 9.24 24.00
#> 72 19 67 17 152 102 82 1 138 198 152.1 121 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 48 19.1 64 62 160 102.1 148 118 84 161 65 198.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 53 200 65.1 196 28 185 104.1 148.1 198.2 135 193 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.2 152.2 34 137 120 34.1 137.1 12 161.1 191 138.1 196.1 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.1 162 132 191.1 122 198.3 118.1 2 116 185.1 75 163 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 83 163.1 62.1 38 146.1 64.1 98 137.2 75.1 83.1 138.2 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 178 126.1 200.1 163.2 182 65.2 95 104.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[21]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003584174 0.405768599 0.297457763
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.18834688 0.01323261 1.07467160
#> grade_iii, Cure model
#> 1.32981345
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 181 16.46 1 45 0 1
#> 190 20.81 1 42 1 0
#> 145 10.07 1 65 1 0
#> 81 14.06 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 184 17.77 1 38 0 0
#> 59 10.16 1 NA 1 0
#> 41 18.02 1 40 1 0
#> 42 12.43 1 49 0 1
#> 149 8.37 1 33 1 0
#> 52 10.42 1 52 0 1
#> 127 3.53 1 62 0 1
#> 90 20.94 1 50 0 1
#> 85 16.44 1 36 0 0
#> 108 18.29 1 39 0 1
#> 101 9.97 1 10 0 1
#> 150 20.33 1 48 0 0
#> 181.1 16.46 1 45 0 1
#> 113 22.86 1 34 0 0
#> 25 6.32 1 34 1 0
#> 129 23.41 1 53 1 0
#> 197 21.60 1 69 1 0
#> 40 18.00 1 28 1 0
#> 8 18.43 1 32 0 0
#> 199 19.81 1 NA 0 1
#> 18 15.21 1 49 1 0
#> 108.1 18.29 1 39 0 1
#> 36 21.19 1 48 0 1
#> 42.1 12.43 1 49 0 1
#> 153 21.33 1 55 1 0
#> 189 10.51 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 106 16.67 1 49 1 0
#> 5 16.43 1 51 0 1
#> 89 11.44 1 NA 0 0
#> 125 15.65 1 67 1 0
#> 4 17.64 1 NA 0 1
#> 63 22.77 1 31 1 0
#> 16 8.71 1 71 0 1
#> 188 16.16 1 46 0 1
#> 139 21.49 1 63 1 0
#> 157 15.10 1 47 0 0
#> 145.1 10.07 1 65 1 0
#> 40.1 18.00 1 28 1 0
#> 61 10.12 1 36 0 1
#> 70 7.38 1 30 1 0
#> 180 14.82 1 37 0 0
#> 91 5.33 1 61 0 1
#> 61.1 10.12 1 36 0 1
#> 189.1 10.51 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 183 9.24 1 67 1 0
#> 18.1 15.21 1 49 1 0
#> 124 9.73 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 136 21.83 1 43 0 1
#> 81.1 14.06 1 34 0 0
#> 124.1 9.73 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 184.1 17.77 1 38 0 0
#> 168 23.72 1 70 0 0
#> 157.1 15.10 1 47 0 0
#> 129.1 23.41 1 53 1 0
#> 167 15.55 1 56 1 0
#> 188.1 16.16 1 46 0 1
#> 154 12.63 1 20 1 0
#> 79 16.23 1 54 1 0
#> 169 22.41 1 46 0 0
#> 164 23.60 1 76 0 1
#> 92 22.92 1 47 0 1
#> 192 16.44 1 31 1 0
#> 16.1 8.71 1 71 0 1
#> 192.1 16.44 1 31 1 0
#> 45 17.42 1 54 0 1
#> 169.1 22.41 1 46 0 0
#> 175 21.91 1 43 0 0
#> 107 11.18 1 54 1 0
#> 194.1 22.40 1 38 0 1
#> 58 19.34 1 39 0 0
#> 90.1 20.94 1 50 0 1
#> 114 13.68 1 NA 0 0
#> 90.2 20.94 1 50 0 1
#> 58.1 19.34 1 39 0 0
#> 154.1 12.63 1 20 1 0
#> 110 17.56 1 65 0 1
#> 45.1 17.42 1 54 0 1
#> 63.1 22.77 1 31 1 0
#> 18.2 15.21 1 49 1 0
#> 175.1 21.91 1 43 0 0
#> 52.1 10.42 1 52 0 1
#> 108.2 18.29 1 39 0 1
#> 18.3 15.21 1 49 1 0
#> 179 18.63 1 42 0 0
#> 76 19.22 1 54 0 1
#> 93 10.33 1 52 0 1
#> 189.2 10.51 1 NA 1 0
#> 49.1 12.19 1 48 1 0
#> 145.2 10.07 1 65 1 0
#> 158 20.14 1 74 1 0
#> 158.1 20.14 1 74 1 0
#> 23 16.92 1 61 0 0
#> 134 17.81 1 47 1 0
#> 99 21.19 1 38 0 1
#> 29 15.45 1 68 1 0
#> 66 22.13 1 53 0 0
#> 56 12.21 1 60 0 0
#> 69 23.23 1 25 0 1
#> 40.2 18.00 1 28 1 0
#> 127.1 3.53 1 62 0 1
#> 68 20.62 1 44 0 0
#> 99.1 21.19 1 38 0 1
#> 80 24.00 0 41 0 0
#> 11 24.00 0 42 0 1
#> 163 24.00 0 66 0 0
#> 82 24.00 0 34 0 0
#> 112 24.00 0 61 0 0
#> 9 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 141 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 94 24.00 0 51 0 1
#> 71 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 135 24.00 0 58 1 0
#> 200 24.00 0 64 0 0
#> 72 24.00 0 40 0 1
#> 44 24.00 0 56 0 0
#> 3 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 35 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 53 24.00 0 32 0 1
#> 47 24.00 0 38 0 1
#> 34 24.00 0 36 0 0
#> 132 24.00 0 55 0 0
#> 141.1 24.00 0 44 1 0
#> 83 24.00 0 6 0 0
#> 142 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 74 24.00 0 43 0 1
#> 151 24.00 0 42 0 0
#> 98 24.00 0 34 1 0
#> 173 24.00 0 19 0 1
#> 67 24.00 0 25 0 0
#> 35.1 24.00 0 51 0 0
#> 82.1 24.00 0 34 0 0
#> 2 24.00 0 9 0 0
#> 71.1 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 172 24.00 0 41 0 0
#> 161 24.00 0 45 0 0
#> 178 24.00 0 52 1 0
#> 82.2 24.00 0 34 0 0
#> 132.1 24.00 0 55 0 0
#> 20 24.00 0 46 1 0
#> 87 24.00 0 27 0 0
#> 62 24.00 0 71 0 0
#> 72.1 24.00 0 40 0 1
#> 75 24.00 0 21 1 0
#> 104 24.00 0 50 1 0
#> 162 24.00 0 51 0 0
#> 34.1 24.00 0 36 0 0
#> 148.1 24.00 0 61 1 0
#> 162.1 24.00 0 51 0 0
#> 20.1 24.00 0 46 1 0
#> 151.1 24.00 0 42 0 0
#> 47.1 24.00 0 38 0 1
#> 196 24.00 0 19 0 0
#> 2.1 24.00 0 9 0 0
#> 119 24.00 0 17 0 0
#> 19 24.00 0 57 0 1
#> 47.2 24.00 0 38 0 1
#> 178.1 24.00 0 52 1 0
#> 35.2 24.00 0 51 0 0
#> 162.2 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 112.1 24.00 0 61 0 0
#> 131 24.00 0 66 0 0
#> 126 24.00 0 48 0 0
#> 38 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 174 24.00 0 49 1 0
#> 142.1 24.00 0 53 0 0
#> 73 24.00 0 NA 0 1
#> 62.1 24.00 0 71 0 0
#> 84.1 24.00 0 39 0 1
#> 161.1 24.00 0 45 0 0
#> 116 24.00 0 58 0 1
#> 104.1 24.00 0 50 1 0
#> 126.1 24.00 0 48 0 0
#> 53.1 24.00 0 32 0 1
#> 67.1 24.00 0 25 0 0
#> 33 24.00 0 53 0 0
#> 9.1 24.00 0 31 1 0
#> 141.2 24.00 0 44 1 0
#> 80.1 24.00 0 41 0 0
#> 191 24.00 0 60 0 1
#> 73.1 24.00 0 NA 0 1
#> 95 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.19 NA NA NA
#> 2 age, Cure model 0.0132 NA NA NA
#> 3 grade_ii, Cure model 1.07 NA NA NA
#> 4 grade_iii, Cure model 1.33 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00358 NA NA NA
#> 2 grade_ii, Survival model 0.406 NA NA NA
#> 3 grade_iii, Survival model 0.297 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.18835 0.01323 1.07467 1.32981
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 241 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.18834688 0.01323261 1.07467160 1.32981345
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003584174 0.405768599 0.297457763
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.560554164 0.294195014 0.884350707 0.747498274 0.811798297 0.482978300
#> [7] 0.434633839 0.784322045 0.946840043 0.839128395 0.982383891 0.264729754
#> [13] 0.579732611 0.405125789 0.911089050 0.314380021 0.560554164 0.084277881
#> [19] 0.964656540 0.037933250 0.202583918 0.444631774 0.394910866 0.674155227
#> [25] 0.405125789 0.234850989 0.784322045 0.224210151 0.738217033 0.550832579
#> [31] 0.607999721 0.645886504 0.096231757 0.929023121 0.627072932 0.213450967
#> [37] 0.710452295 0.884350707 0.444631774 0.866330842 0.955762717 0.728912839
#> [43] 0.973523524 0.866330842 0.344383298 0.920063956 0.674155227 0.138399541
#> [49] 0.191616015 0.747498274 0.512003184 0.482978300 0.006026546 0.710452295
#> [55] 0.037933250 0.655337832 0.627072932 0.765997915 0.617553734 0.117022613
#> [61] 0.021787699 0.072517827 0.579732611 0.929023121 0.579732611 0.521778063
#> [67] 0.117022613 0.170124375 0.830000589 0.138399541 0.354494379 0.264729754
#> [73] 0.264729754 0.354494379 0.765997915 0.502273612 0.521778063 0.096231757
#> [79] 0.674155227 0.170124375 0.839128395 0.405125789 0.674155227 0.384724508
#> [85] 0.374575715 0.857238697 0.811798297 0.884350707 0.324548703 0.324548703
#> [91] 0.541066395 0.473282188 0.234850989 0.664758241 0.159221088 0.802590896
#> [97] 0.060494328 0.444631774 0.982383891 0.304263083 0.234850989 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 181 190 145 81 49 184 41 42 149 52 127 90 85
#> 16.46 20.81 10.07 14.06 12.19 17.77 18.02 12.43 8.37 10.42 3.53 20.94 16.44
#> 108 101 150 181.1 113 25 129 197 40 8 18 108.1 36
#> 18.29 9.97 20.33 16.46 22.86 6.32 23.41 21.60 18.00 18.43 15.21 18.29 21.19
#> 42.1 153 96 106 5 125 63 16 188 139 157 145.1 40.1
#> 12.43 21.33 14.54 16.67 16.43 15.65 22.77 8.71 16.16 21.49 15.10 10.07 18.00
#> 61 70 180 91 61.1 166 183 18.1 194 136 81.1 30 184.1
#> 10.12 7.38 14.82 5.33 10.12 19.98 9.24 15.21 22.40 21.83 14.06 17.43 17.77
#> 168 157.1 129.1 167 188.1 154 79 169 164 92 192 16.1 192.1
#> 23.72 15.10 23.41 15.55 16.16 12.63 16.23 22.41 23.60 22.92 16.44 8.71 16.44
#> 45 169.1 175 107 194.1 58 90.1 90.2 58.1 154.1 110 45.1 63.1
#> 17.42 22.41 21.91 11.18 22.40 19.34 20.94 20.94 19.34 12.63 17.56 17.42 22.77
#> 18.2 175.1 52.1 108.2 18.3 179 76 93 49.1 145.2 158 158.1 23
#> 15.21 21.91 10.42 18.29 15.21 18.63 19.22 10.33 12.19 10.07 20.14 20.14 16.92
#> 134 99 29 66 56 69 40.2 127.1 68 99.1 80 11 163
#> 17.81 21.19 15.45 22.13 12.21 23.23 18.00 3.53 20.62 21.19 24.00 24.00 24.00
#> 82 112 9 152 141 146 94 71 64 135 200 72 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 46 35 121 53 47 34 132 141.1 83 142 148 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 98 173 67 35.1 82.1 2 71.1 27 172 161 178 82.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 20 87 62 72.1 75 104 162 34.1 148.1 162.1 20.1 151.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.1 196 2.1 119 19 47.2 178.1 35.2 162.2 1 112.1 131 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 84 174 142.1 62.1 84.1 161.1 116 104.1 126.1 53.1 67.1 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 141.2 80.1 191 95
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[22]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01318131 0.54265599 0.17910662
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.221053719 -0.008552367 0.454132395
#> grade_iii, Cure model
#> 0.706633003
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 8 18.43 1 32 0 0
#> 4 17.64 1 NA 0 1
#> 41 18.02 1 40 1 0
#> 92 22.92 1 47 0 1
#> 167 15.55 1 56 1 0
#> 159 10.55 1 50 0 1
#> 150 20.33 1 48 0 0
#> 70 7.38 1 30 1 0
#> 92.1 22.92 1 47 0 1
#> 169 22.41 1 46 0 0
#> 79 16.23 1 54 1 0
#> 105 19.75 1 60 0 0
#> 70.1 7.38 1 30 1 0
#> 175 21.91 1 43 0 0
#> 145 10.07 1 65 1 0
#> 106 16.67 1 49 1 0
#> 159.1 10.55 1 50 0 1
#> 127 3.53 1 62 0 1
#> 10 10.53 1 34 0 0
#> 99 21.19 1 38 0 1
#> 49 12.19 1 48 1 0
#> 150.1 20.33 1 48 0 0
#> 58 19.34 1 39 0 0
#> 15 22.68 1 48 0 0
#> 157 15.10 1 47 0 0
#> 179 18.63 1 42 0 0
#> 113 22.86 1 34 0 0
#> 180 14.82 1 37 0 0
#> 181 16.46 1 45 0 1
#> 29 15.45 1 68 1 0
#> 197 21.60 1 69 1 0
#> 69 23.23 1 25 0 1
#> 90 20.94 1 50 0 1
#> 92.2 22.92 1 47 0 1
#> 86 23.81 1 58 0 1
#> 32 20.90 1 37 1 0
#> 153 21.33 1 55 1 0
#> 169.1 22.41 1 46 0 0
#> 40 18.00 1 28 1 0
#> 77 7.27 1 67 0 1
#> 194 22.40 1 38 0 1
#> 43 12.10 1 61 0 1
#> 78 23.88 1 43 0 0
#> 41.1 18.02 1 40 1 0
#> 13 14.34 1 54 0 1
#> 159.2 10.55 1 50 0 1
#> 197.1 21.60 1 69 1 0
#> 32.1 20.90 1 37 1 0
#> 106.1 16.67 1 49 1 0
#> 123 13.00 1 44 1 0
#> 45 17.42 1 54 0 1
#> 149 8.37 1 33 1 0
#> 32.2 20.90 1 37 1 0
#> 39 15.59 1 37 0 1
#> 181.1 16.46 1 45 0 1
#> 32.3 20.90 1 37 1 0
#> 153.1 21.33 1 55 1 0
#> 117 17.46 1 26 0 1
#> 81 14.06 1 34 0 0
#> 69.1 23.23 1 25 0 1
#> 96 14.54 1 33 0 1
#> 90.1 20.94 1 50 0 1
#> 61 10.12 1 36 0 1
#> 179.1 18.63 1 42 0 0
#> 170 19.54 1 43 0 1
#> 42 12.43 1 49 0 1
#> 114 13.68 1 NA 0 0
#> 89 11.44 1 NA 0 0
#> 108 18.29 1 39 0 1
#> 96.1 14.54 1 33 0 1
#> 145.1 10.07 1 65 1 0
#> 14 12.89 1 21 0 0
#> 24 23.89 1 38 0 0
#> 184 17.77 1 38 0 0
#> 155 13.08 1 26 0 0
#> 117.1 17.46 1 26 0 1
#> 105.1 19.75 1 60 0 0
#> 139 21.49 1 63 1 0
#> 68 20.62 1 44 0 0
#> 179.2 18.63 1 42 0 0
#> 49.1 12.19 1 48 1 0
#> 159.3 10.55 1 50 0 1
#> 91 5.33 1 61 0 1
#> 180.1 14.82 1 37 0 0
#> 26 15.77 1 49 0 1
#> 18 15.21 1 49 1 0
#> 114.1 13.68 1 NA 0 0
#> 14.1 12.89 1 21 0 0
#> 192 16.44 1 31 1 0
#> 100 16.07 1 60 0 0
#> 16 8.71 1 71 0 1
#> 123.1 13.00 1 44 1 0
#> 86.1 23.81 1 58 0 1
#> 149.1 8.37 1 33 1 0
#> 179.3 18.63 1 42 0 0
#> 26.1 15.77 1 49 0 1
#> 61.1 10.12 1 36 0 1
#> 190 20.81 1 42 1 0
#> 100.1 16.07 1 60 0 0
#> 39.1 15.59 1 37 0 1
#> 154 12.63 1 20 1 0
#> 164 23.60 1 76 0 1
#> 129 23.41 1 53 1 0
#> 139.1 21.49 1 63 1 0
#> 154.1 12.63 1 20 1 0
#> 66 22.13 1 53 0 0
#> 86.2 23.81 1 58 0 1
#> 184.1 17.77 1 38 0 0
#> 77.1 7.27 1 67 0 1
#> 187 9.92 1 39 1 0
#> 134 17.81 1 47 1 0
#> 59 10.16 1 NA 1 0
#> 182 24.00 0 35 0 0
#> 103 24.00 0 56 1 0
#> 95 24.00 0 68 0 1
#> 17 24.00 0 38 0 1
#> 94 24.00 0 51 0 1
#> 7 24.00 0 37 1 0
#> 196 24.00 0 19 0 0
#> 46 24.00 0 71 0 0
#> 38 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 21 24.00 0 47 0 0
#> 142 24.00 0 53 0 0
#> 156 24.00 0 50 1 0
#> 7.1 24.00 0 37 1 0
#> 12 24.00 0 63 0 0
#> 34 24.00 0 36 0 0
#> 141 24.00 0 44 1 0
#> 7.2 24.00 0 37 1 0
#> 87.1 24.00 0 27 0 0
#> 196.1 24.00 0 19 0 0
#> 33 24.00 0 53 0 0
#> 54 24.00 0 53 1 0
#> 3 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 72 24.00 0 40 0 1
#> 126 24.00 0 48 0 0
#> 132 24.00 0 55 0 0
#> 115 24.00 0 NA 1 0
#> 1 24.00 0 23 1 0
#> 3.1 24.00 0 31 1 0
#> 33.1 24.00 0 53 0 0
#> 28 24.00 0 67 1 0
#> 67 24.00 0 25 0 0
#> 138 24.00 0 44 1 0
#> 196.2 24.00 0 19 0 0
#> 118 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 116 24.00 0 58 0 1
#> 74 24.00 0 43 0 1
#> 46.1 24.00 0 71 0 0
#> 120 24.00 0 68 0 1
#> 178 24.00 0 52 1 0
#> 112 24.00 0 61 0 0
#> 152 24.00 0 36 0 1
#> 75 24.00 0 21 1 0
#> 17.1 24.00 0 38 0 1
#> 120.1 24.00 0 68 0 1
#> 20 24.00 0 46 1 0
#> 148 24.00 0 61 1 0
#> 48 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 165 24.00 0 47 0 0
#> 176 24.00 0 43 0 1
#> 162 24.00 0 51 0 0
#> 17.2 24.00 0 38 0 1
#> 74.1 24.00 0 43 0 1
#> 47 24.00 0 38 0 1
#> 161 24.00 0 45 0 0
#> 19 24.00 0 57 0 1
#> 7.3 24.00 0 37 1 0
#> 172 24.00 0 41 0 0
#> 132.1 24.00 0 55 0 0
#> 21.1 24.00 0 47 0 0
#> 7.4 24.00 0 37 1 0
#> 27 24.00 0 63 1 0
#> 95.1 24.00 0 68 0 1
#> 132.2 24.00 0 55 0 0
#> 74.2 24.00 0 43 0 1
#> 46.2 24.00 0 71 0 0
#> 120.2 24.00 0 68 0 1
#> 28.1 24.00 0 67 1 0
#> 196.3 24.00 0 19 0 0
#> 146 24.00 0 63 1 0
#> 196.4 24.00 0 19 0 0
#> 118.1 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 193 24.00 0 45 0 1
#> 126.1 24.00 0 48 0 0
#> 116.1 24.00 0 58 0 1
#> 84 24.00 0 39 0 1
#> 142.1 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 80 24.00 0 41 0 0
#> 64 24.00 0 43 0 0
#> 162.1 24.00 0 51 0 0
#> 143 24.00 0 51 0 0
#> 196.5 24.00 0 19 0 0
#> 47.1 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.221 NA NA NA
#> 2 age, Cure model -0.00855 NA NA NA
#> 3 grade_ii, Cure model 0.454 NA NA NA
#> 4 grade_iii, Cure model 0.707 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0132 NA NA NA
#> 2 grade_ii, Survival model 0.543 NA NA NA
#> 3 grade_iii, Survival model 0.179 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.221054 -0.008552 0.454132 0.706633
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 262.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.221053719 -0.008552367 0.454132395 0.706633003
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01318131 0.54265599 0.17910662
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.2914334049 0.3110609915 0.0297407221 0.5258652257 0.7671195304
#> [6] 0.2023777962 0.9252354433 0.0297407221 0.0550264188 0.4511550291
#> [11] 0.2190989127 0.9252354433 0.0805025483 0.8511406704 0.3999410529
#> [16] 0.7671195304 0.9873173999 0.8145578360 0.1318625657 0.7318994417
#> [21] 0.2023777962 0.2455486804 0.0492158525 0.5590552602 0.2546837986
#> [26] 0.0437104111 0.5702585803 0.4201896221 0.5368761034 0.0875965602
#> [31] 0.0211405139 0.1397950963 0.0297407221 0.0042636777 0.1558876187
#> [36] 0.1167178030 0.0550264188 0.3304487352 0.9498104939 0.0671406513
#> [41] 0.7552610656 0.0018182197 0.3110609915 0.6155032730 0.7671195304
#> [46] 0.0875965602 0.1558876187 0.3999410529 0.6503868781 0.3897367107
#> [51] 0.9005564728 0.1558876187 0.5041539080 0.4201896221 0.1558876187
#> [56] 0.1167178030 0.3698078476 0.6270589129 0.0211405139 0.5927834336
#> [61] 0.1397950963 0.8267511602 0.2546837986 0.2365481738 0.7201564713
#> [66] 0.3012016822 0.5927834336 0.8511406704 0.6735967509 0.0003491229
#> [71] 0.3500399798 0.6386919901 0.3698078476 0.2190989127 0.1018957822
#> [76] 0.1941624675 0.2546837986 0.7318994417 0.7671195304 0.9747111886
#> [81] 0.5702585803 0.4826881525 0.5479546723 0.6735967509 0.4407746329
#> [86] 0.4615727322 0.8880921921 0.6503868781 0.0042636777 0.9005564728
#> [91] 0.2546837986 0.4826881525 0.8267511602 0.1860973464 0.4615727322
#> [96] 0.5041539080 0.6970016852 0.0122435286 0.0166028855 0.1018957822
#> [101] 0.6970016852 0.0736692795 0.0042636777 0.3500399798 0.9498104939
#> [106] 0.8757200848 0.3402339156 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 8 41 92 167 159 150 70 92.1 169 79 105 70.1 175
#> 18.43 18.02 22.92 15.55 10.55 20.33 7.38 22.92 22.41 16.23 19.75 7.38 21.91
#> 145 106 159.1 127 10 99 49 150.1 58 15 157 179 113
#> 10.07 16.67 10.55 3.53 10.53 21.19 12.19 20.33 19.34 22.68 15.10 18.63 22.86
#> 180 181 29 197 69 90 92.2 86 32 153 169.1 40 77
#> 14.82 16.46 15.45 21.60 23.23 20.94 22.92 23.81 20.90 21.33 22.41 18.00 7.27
#> 194 43 78 41.1 13 159.2 197.1 32.1 106.1 123 45 149 32.2
#> 22.40 12.10 23.88 18.02 14.34 10.55 21.60 20.90 16.67 13.00 17.42 8.37 20.90
#> 39 181.1 32.3 153.1 117 81 69.1 96 90.1 61 179.1 170 42
#> 15.59 16.46 20.90 21.33 17.46 14.06 23.23 14.54 20.94 10.12 18.63 19.54 12.43
#> 108 96.1 145.1 14 24 184 155 117.1 105.1 139 68 179.2 49.1
#> 18.29 14.54 10.07 12.89 23.89 17.77 13.08 17.46 19.75 21.49 20.62 18.63 12.19
#> 159.3 91 180.1 26 18 14.1 192 100 16 123.1 86.1 149.1 179.3
#> 10.55 5.33 14.82 15.77 15.21 12.89 16.44 16.07 8.71 13.00 23.81 8.37 18.63
#> 26.1 61.1 190 100.1 39.1 154 164 129 139.1 154.1 66 86.2 184.1
#> 15.77 10.12 20.81 16.07 15.59 12.63 23.60 23.41 21.49 12.63 22.13 23.81 17.77
#> 77.1 187 134 182 103 95 17 94 7 196 46 38 87
#> 7.27 9.92 17.81 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 142 156 7.1 12 34 141 7.2 87.1 196.1 33 54 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 72 126 132 1 3.1 33.1 28 67 138 196.2 118 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 74 46.1 120 178 112 152 75 17.1 120.1 20 148 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 165 176 162 17.2 74.1 47 161 19 7.3 172 132.1 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.4 27 95.1 132.2 74.2 46.2 120.2 28.1 196.3 146 196.4 118.1 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 126.1 116.1 84 142.1 198 80 64 162.1 143 196.5 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[23]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003711743 0.369737682 0.433539370
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.385207395 -0.007175742 0.164989830
#> grade_iii, Cure model
#> 0.218251416
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 56 12.21 1 60 0 0
#> 13 14.34 1 54 0 1
#> 45 17.42 1 54 0 1
#> 184 17.77 1 38 0 0
#> 66 22.13 1 53 0 0
#> 110 17.56 1 65 0 1
#> 130 16.47 1 53 0 1
#> 149 8.37 1 33 1 0
#> 26 15.77 1 49 0 1
#> 117 17.46 1 26 0 1
#> 139 21.49 1 63 1 0
#> 39 15.59 1 37 0 1
#> 68 20.62 1 44 0 0
#> 5 16.43 1 51 0 1
#> 41 18.02 1 40 1 0
#> 81 14.06 1 34 0 0
#> 157 15.10 1 47 0 0
#> 18 15.21 1 49 1 0
#> 6 15.64 1 39 0 0
#> 114 13.68 1 NA 0 0
#> 6.1 15.64 1 39 0 0
#> 15 22.68 1 48 0 0
#> 129 23.41 1 53 1 0
#> 124 9.73 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 140 12.68 1 59 1 0
#> 106 16.67 1 49 1 0
#> 199 19.81 1 NA 0 1
#> 183 9.24 1 67 1 0
#> 60 13.15 1 38 1 0
#> 45.1 17.42 1 54 0 1
#> 139.1 21.49 1 63 1 0
#> 180 14.82 1 37 0 0
#> 50 10.02 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 167 15.55 1 56 1 0
#> 106.1 16.67 1 49 1 0
#> 197 21.60 1 69 1 0
#> 157.1 15.10 1 47 0 0
#> 113 22.86 1 34 0 0
#> 30 17.43 1 78 0 0
#> 89 11.44 1 NA 0 0
#> 81.1 14.06 1 34 0 0
#> 4 17.64 1 NA 0 1
#> 189 10.51 1 NA 1 0
#> 190 20.81 1 42 1 0
#> 107 11.18 1 54 1 0
#> 99 21.19 1 38 0 1
#> 130.1 16.47 1 53 0 1
#> 63 22.77 1 31 1 0
#> 52 10.42 1 52 0 1
#> 51.1 18.23 1 83 0 1
#> 199.1 19.81 1 NA 0 1
#> 40.1 18.00 1 28 1 0
#> 168 23.72 1 70 0 0
#> 136 21.83 1 43 0 1
#> 101 9.97 1 10 0 1
#> 78 23.88 1 43 0 0
#> 14 12.89 1 21 0 0
#> 117.1 17.46 1 26 0 1
#> 89.1 11.44 1 NA 0 0
#> 51.2 18.23 1 83 0 1
#> 134 17.81 1 47 1 0
#> 37 12.52 1 57 1 0
#> 10 10.53 1 34 0 0
#> 55 19.34 1 69 0 1
#> 133 14.65 1 57 0 0
#> 86 23.81 1 58 0 1
#> 37.1 12.52 1 57 1 0
#> 133.1 14.65 1 57 0 0
#> 99.1 21.19 1 38 0 1
#> 25 6.32 1 34 1 0
#> 55.1 19.34 1 69 0 1
#> 190.1 20.81 1 42 1 0
#> 68.1 20.62 1 44 0 0
#> 24 23.89 1 38 0 0
#> 124.1 9.73 1 NA 1 0
#> 25.1 6.32 1 34 1 0
#> 111 17.45 1 47 0 1
#> 63.1 22.77 1 31 1 0
#> 88 18.37 1 47 0 0
#> 184.1 17.77 1 38 0 0
#> 99.2 21.19 1 38 0 1
#> 117.2 17.46 1 26 0 1
#> 183.1 9.24 1 67 1 0
#> 113.1 22.86 1 34 0 0
#> 150 20.33 1 48 0 0
#> 41.1 18.02 1 40 1 0
#> 140.1 12.68 1 59 1 0
#> 32 20.90 1 37 1 0
#> 188 16.16 1 46 0 1
#> 10.1 10.53 1 34 0 0
#> 41.2 18.02 1 40 1 0
#> 149.1 8.37 1 33 1 0
#> 96 14.54 1 33 0 1
#> 129.1 23.41 1 53 1 0
#> 108 18.29 1 39 0 1
#> 57 14.46 1 45 0 1
#> 32.1 20.90 1 37 1 0
#> 199.2 19.81 1 NA 0 1
#> 78.1 23.88 1 43 0 0
#> 158 20.14 1 74 1 0
#> 187 9.92 1 39 1 0
#> 93 10.33 1 52 0 1
#> 101.1 9.97 1 10 0 1
#> 59 10.16 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 140.2 12.68 1 59 1 0
#> 177 12.53 1 75 0 0
#> 4.1 17.64 1 NA 0 1
#> 175 21.91 1 43 0 0
#> 100.1 16.07 1 60 0 0
#> 73 24.00 0 NA 0 1
#> 135 24.00 0 58 1 0
#> 126 24.00 0 48 0 0
#> 161 24.00 0 45 0 0
#> 74 24.00 0 43 0 1
#> 65 24.00 0 57 1 0
#> 48 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 17 24.00 0 38 0 1
#> 72 24.00 0 40 0 1
#> 185 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 94 24.00 0 51 0 1
#> 1 24.00 0 23 1 0
#> 46 24.00 0 71 0 0
#> 98 24.00 0 34 1 0
#> 186 24.00 0 45 1 0
#> 83 24.00 0 6 0 0
#> 80 24.00 0 41 0 0
#> 73.1 24.00 0 NA 0 1
#> 94.1 24.00 0 51 0 1
#> 53 24.00 0 32 0 1
#> 98.1 24.00 0 34 1 0
#> 131 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 35 24.00 0 51 0 0
#> 72.1 24.00 0 40 0 1
#> 173 24.00 0 19 0 1
#> 118 24.00 0 44 1 0
#> 46.1 24.00 0 71 0 0
#> 186.1 24.00 0 45 1 0
#> 98.2 24.00 0 34 1 0
#> 115 24.00 0 NA 1 0
#> 116 24.00 0 58 0 1
#> 74.1 24.00 0 43 0 1
#> 137 24.00 0 45 1 0
#> 38 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 143 24.00 0 51 0 0
#> 71 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 165 24.00 0 47 0 0
#> 116.1 24.00 0 58 0 1
#> 182 24.00 0 35 0 0
#> 11 24.00 0 42 0 1
#> 135.1 24.00 0 58 1 0
#> 143.1 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 95 24.00 0 68 0 1
#> 193 24.00 0 45 0 1
#> 34 24.00 0 36 0 0
#> 198 24.00 0 66 0 1
#> 148 24.00 0 61 1 0
#> 116.2 24.00 0 58 0 1
#> 73.2 24.00 0 NA 0 1
#> 148.1 24.00 0 61 1 0
#> 147.1 24.00 0 76 1 0
#> 3 24.00 0 31 1 0
#> 178.1 24.00 0 52 1 0
#> 46.2 24.00 0 71 0 0
#> 31 24.00 0 36 0 1
#> 3.1 24.00 0 31 1 0
#> 198.1 24.00 0 66 0 1
#> 75 24.00 0 21 1 0
#> 176 24.00 0 43 0 1
#> 102 24.00 0 49 0 0
#> 2 24.00 0 9 0 0
#> 200 24.00 0 64 0 0
#> 54 24.00 0 53 1 0
#> 46.3 24.00 0 71 0 0
#> 46.4 24.00 0 71 0 0
#> 152.1 24.00 0 36 0 1
#> 162 24.00 0 51 0 0
#> 174 24.00 0 49 1 0
#> 95.1 24.00 0 68 0 1
#> 163 24.00 0 66 0 0
#> 64 24.00 0 43 0 0
#> 185.1 24.00 0 44 1 0
#> 200.1 24.00 0 64 0 0
#> 143.2 24.00 0 51 0 0
#> 120 24.00 0 68 0 1
#> 186.2 24.00 0 45 1 0
#> 196 24.00 0 19 0 0
#> 46.5 24.00 0 71 0 0
#> 163.1 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 120.1 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.385 NA NA NA
#> 2 age, Cure model -0.00718 NA NA NA
#> 3 grade_ii, Cure model 0.165 NA NA NA
#> 4 grade_iii, Cure model 0.218 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00371 NA NA NA
#> 2 grade_ii, Survival model 0.370 NA NA NA
#> 3 grade_iii, Survival model 0.434 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.385207 -0.007176 0.164990 0.218251
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 252.5
#> Residual Deviance: 251.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.385207395 -0.007175742 0.164989830 0.218251416
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003711743 0.369737682 0.433539370
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.863451338 0.761912359 0.546464911 0.468905518 0.151149689 0.488658668
#> [7] 0.584375662 0.964147017 0.640533785 0.498594119 0.199404557 0.668578158
#> [13] 0.295416504 0.603103721 0.409585909 0.771212277 0.696581891 0.687272283
#> [19] 0.649902907 0.649902907 0.139203837 0.069607894 0.379383653 0.808354903
#> [25] 0.565485908 0.946080972 0.789752681 0.546464911 0.199404557 0.715155656
#> [31] 0.439247702 0.677936542 0.565485908 0.187507286 0.696581891 0.092756282
#> [37] 0.536780948 0.771212277 0.274742127 0.872709908 0.222109961 0.584375662
#> [43] 0.116640050 0.900380108 0.379383653 0.439247702 0.055977073 0.175518770
#> [49] 0.918828002 0.019802324 0.799049732 0.498594119 0.379383653 0.458978344
#> [55] 0.845072611 0.881950393 0.337646474 0.724519341 0.043076525 0.845072611
#> [61] 0.724519341 0.222109961 0.982118618 0.337646474 0.274742127 0.295416504
#> [67] 0.006260884 0.982118618 0.527140707 0.116640050 0.358361405 0.468905518
#> [73] 0.222109961 0.498594119 0.946080972 0.092756282 0.316311735 0.409585909
#> [79] 0.808354903 0.253690998 0.612500917 0.881950393 0.409585909 0.964147017
#> [85] 0.743217280 0.069607894 0.368922646 0.752582547 0.253690998 0.019802324
#> [91] 0.326996441 0.936981948 0.909616772 0.918828002 0.621854981 0.808354903
#> [97] 0.835797987 0.163266980 0.621854981 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 56 13 45 184 66 110 130 149 26 117 139 39 68
#> 12.21 14.34 17.42 17.77 22.13 17.56 16.47 8.37 15.77 17.46 21.49 15.59 20.62
#> 5 41 81 157 18 6 6.1 15 129 51 140 106 183
#> 16.43 18.02 14.06 15.10 15.21 15.64 15.64 22.68 23.41 18.23 12.68 16.67 9.24
#> 60 45.1 139.1 180 40 167 106.1 197 157.1 113 30 81.1 190
#> 13.15 17.42 21.49 14.82 18.00 15.55 16.67 21.60 15.10 22.86 17.43 14.06 20.81
#> 107 99 130.1 63 52 51.1 40.1 168 136 101 78 14 117.1
#> 11.18 21.19 16.47 22.77 10.42 18.23 18.00 23.72 21.83 9.97 23.88 12.89 17.46
#> 51.2 134 37 10 55 133 86 37.1 133.1 99.1 25 55.1 190.1
#> 18.23 17.81 12.52 10.53 19.34 14.65 23.81 12.52 14.65 21.19 6.32 19.34 20.81
#> 68.1 24 25.1 111 63.1 88 184.1 99.2 117.2 183.1 113.1 150 41.1
#> 20.62 23.89 6.32 17.45 22.77 18.37 17.77 21.19 17.46 9.24 22.86 20.33 18.02
#> 140.1 32 188 10.1 41.2 149.1 96 129.1 108 57 32.1 78.1 158
#> 12.68 20.90 16.16 10.53 18.02 8.37 14.54 23.41 18.29 14.46 20.90 23.88 20.14
#> 187 93 101.1 100 140.2 177 175 100.1 135 126 161 74 65
#> 9.92 10.33 9.97 16.07 12.68 12.53 21.91 16.07 24.00 24.00 24.00 24.00 24.00
#> 48 138 112 17 72 185 9 94 1 46 98 186 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 94.1 53 98.1 131 147 35 72.1 173 118 46.1 186.1 98.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 74.1 137 38 152 143 71 44 165 116.1 182 11 135.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143.1 178 95 193 34 198 148 116.2 148.1 147.1 3 178.1 46.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 3.1 198.1 75 176 102 2 200 54 46.3 46.4 152.1 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 95.1 163 64 185.1 200.1 143.2 120 186.2 196 46.5 163.1 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[24]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005912359 0.736641743 0.369666122
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.76642795 0.02142552 -0.44378810
#> grade_iii, Cure model
#> 0.19910501
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 175 21.91 1 43 0 0
#> 99 21.19 1 38 0 1
#> 89 11.44 1 NA 0 0
#> 136 21.83 1 43 0 1
#> 49 12.19 1 48 1 0
#> 177 12.53 1 75 0 0
#> 77 7.27 1 67 0 1
#> 100 16.07 1 60 0 0
#> 114 13.68 1 NA 0 0
#> 169 22.41 1 46 0 0
#> 114.1 13.68 1 NA 0 0
#> 57 14.46 1 45 0 1
#> 113 22.86 1 34 0 0
#> 42 12.43 1 49 0 1
#> 57.1 14.46 1 45 0 1
#> 18 15.21 1 49 1 0
#> 123 13.00 1 44 1 0
#> 100.1 16.07 1 60 0 0
#> 110 17.56 1 65 0 1
#> 86 23.81 1 58 0 1
#> 89.1 11.44 1 NA 0 0
#> 188 16.16 1 46 0 1
#> 26 15.77 1 49 0 1
#> 18.1 15.21 1 49 1 0
#> 179 18.63 1 42 0 0
#> 96 14.54 1 33 0 1
#> 195 11.76 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 91 5.33 1 61 0 1
#> 58 19.34 1 39 0 0
#> 149 8.37 1 33 1 0
#> 77.1 7.27 1 67 0 1
#> 56 12.21 1 60 0 0
#> 5 16.43 1 51 0 1
#> 86.1 23.81 1 58 0 1
#> 159 10.55 1 50 0 1
#> 36 21.19 1 48 0 1
#> 153 21.33 1 55 1 0
#> 25 6.32 1 34 1 0
#> 145 10.07 1 65 1 0
#> 129 23.41 1 53 1 0
#> 61 10.12 1 36 0 1
#> 181 16.46 1 45 0 1
#> 139 21.49 1 63 1 0
#> 195.1 11.76 1 NA 1 0
#> 114.2 13.68 1 NA 0 0
#> 37 12.52 1 57 1 0
#> 134 17.81 1 47 1 0
#> 157 15.10 1 47 0 0
#> 99.1 21.19 1 38 0 1
#> 29 15.45 1 68 1 0
#> 60 13.15 1 38 1 0
#> 179.1 18.63 1 42 0 0
#> 110.1 17.56 1 65 0 1
#> 175.1 21.91 1 43 0 0
#> 13 14.34 1 54 0 1
#> 111 17.45 1 47 0 1
#> 6 15.64 1 39 0 0
#> 4 17.64 1 NA 0 1
#> 16 8.71 1 71 0 1
#> 183 9.24 1 67 1 0
#> 100.2 16.07 1 60 0 0
#> 18.2 15.21 1 49 1 0
#> 124 9.73 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 24.1 23.89 1 38 0 0
#> 199 19.81 1 NA 0 1
#> 85 16.44 1 36 0 0
#> 66 22.13 1 53 0 0
#> 199.1 19.81 1 NA 0 1
#> 166 19.98 1 48 0 0
#> 184 17.77 1 38 0 0
#> 49.1 12.19 1 48 1 0
#> 154 12.63 1 20 1 0
#> 124.1 9.73 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 149.1 8.37 1 33 1 0
#> 155 13.08 1 26 0 0
#> 18.3 15.21 1 49 1 0
#> 190 20.81 1 42 1 0
#> 32 20.90 1 37 1 0
#> 50 10.02 1 NA 1 0
#> 90.1 20.94 1 50 0 1
#> 154.1 12.63 1 20 1 0
#> 58.1 19.34 1 39 0 0
#> 15 22.68 1 48 0 0
#> 133 14.65 1 57 0 0
#> 158.1 20.14 1 74 1 0
#> 66.1 22.13 1 53 0 0
#> 68 20.62 1 44 0 0
#> 169.1 22.41 1 46 0 0
#> 56.1 12.21 1 60 0 0
#> 177.1 12.53 1 75 0 0
#> 76 19.22 1 54 0 1
#> 23 16.92 1 61 0 0
#> 36.1 21.19 1 48 0 1
#> 57.2 14.46 1 45 0 1
#> 76.1 19.22 1 54 0 1
#> 113.1 22.86 1 34 0 0
#> 123.1 13.00 1 44 1 0
#> 99.2 21.19 1 38 0 1
#> 92 22.92 1 47 0 1
#> 114.3 13.68 1 NA 0 0
#> 169.2 22.41 1 46 0 0
#> 91.1 5.33 1 61 0 1
#> 81 14.06 1 34 0 0
#> 36.2 21.19 1 48 0 1
#> 140 12.68 1 59 1 0
#> 159.1 10.55 1 50 0 1
#> 45 17.42 1 54 0 1
#> 52 10.42 1 52 0 1
#> 51 18.23 1 83 0 1
#> 191 24.00 0 60 0 1
#> 104 24.00 0 50 1 0
#> 137 24.00 0 45 1 0
#> 20 24.00 0 46 1 0
#> 152 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 152.1 24.00 0 36 0 1
#> 142 24.00 0 53 0 0
#> 109 24.00 0 48 0 0
#> 109.1 24.00 0 48 0 0
#> 115 24.00 0 NA 1 0
#> 28 24.00 0 67 1 0
#> 31 24.00 0 36 0 1
#> 3 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 47 24.00 0 38 0 1
#> 83 24.00 0 6 0 0
#> 22 24.00 0 52 1 0
#> 146 24.00 0 63 1 0
#> 83.1 24.00 0 6 0 0
#> 176 24.00 0 43 0 1
#> 165 24.00 0 47 0 0
#> 75 24.00 0 21 1 0
#> 38 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 46 24.00 0 71 0 0
#> 165.1 24.00 0 47 0 0
#> 121 24.00 0 57 1 0
#> 156 24.00 0 50 1 0
#> 48 24.00 0 31 1 0
#> 121.1 24.00 0 57 1 0
#> 191.1 24.00 0 60 0 1
#> 191.2 24.00 0 60 0 1
#> 115.1 24.00 0 NA 1 0
#> 104.1 24.00 0 50 1 0
#> 73 24.00 0 NA 0 1
#> 71 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 28.1 24.00 0 67 1 0
#> 135 24.00 0 58 1 0
#> 173 24.00 0 19 0 1
#> 120 24.00 0 68 0 1
#> 161 24.00 0 45 0 0
#> 9 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 20.1 24.00 0 46 1 0
#> 160 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 33 24.00 0 53 0 0
#> 131 24.00 0 66 0 0
#> 104.2 24.00 0 50 1 0
#> 163 24.00 0 66 0 0
#> 80 24.00 0 41 0 0
#> 21 24.00 0 47 0 0
#> 67 24.00 0 25 0 0
#> 132.1 24.00 0 55 0 0
#> 115.2 24.00 0 NA 1 0
#> 47.1 24.00 0 38 0 1
#> 126 24.00 0 48 0 0
#> 152.2 24.00 0 36 0 1
#> 143 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 103 24.00 0 56 1 0
#> 198 24.00 0 66 0 1
#> 186 24.00 0 45 1 0
#> 53 24.00 0 32 0 1
#> 3.1 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 94 24.00 0 51 0 1
#> 138 24.00 0 44 1 0
#> 83.2 24.00 0 6 0 0
#> 7 24.00 0 37 1 0
#> 115.3 24.00 0 NA 1 0
#> 120.1 24.00 0 68 0 1
#> 80.1 24.00 0 41 0 0
#> 198.1 24.00 0 66 0 1
#> 94.1 24.00 0 51 0 1
#> 48.1 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 64 24.00 0 43 0 0
#> 3.2 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 31.1 24.00 0 36 0 1
#> 138.1 24.00 0 44 1 0
#> 146.1 24.00 0 63 1 0
#> 7.1 24.00 0 37 1 0
#> 17 24.00 0 38 0 1
#> 94.2 24.00 0 51 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.766 NA NA NA
#> 2 age, Cure model 0.0214 NA NA NA
#> 3 grade_ii, Cure model -0.444 NA NA NA
#> 4 grade_iii, Cure model 0.199 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00591 NA NA NA
#> 2 grade_ii, Survival model 0.737 NA NA NA
#> 3 grade_iii, Survival model 0.370 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.76643 0.02143 -0.44379 0.19911
#>
#> Degrees of Freedom: 180 Total (i.e. Null); 177 Residual
#> Null Deviance: 249.7
#> Residual Deviance: 242.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.76642795 0.02142552 -0.44378810 0.19910501
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005912359 0.736641743 0.369666122
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.35144548 0.42303395 0.38149571 0.91346206 0.87822886 0.97410064
#> [7] 0.71176190 0.27394319 0.80264975 0.22181272 0.89600628 0.80264975
#> [13] 0.75587798 0.84774451 0.71176190 0.64152748 0.13482225 0.70420137
#> [19] 0.73390620 0.75587798 0.59926944 0.79598201 0.53688825 0.98974916
#> [25] 0.56407133 0.96351829 0.97410064 0.90185884 0.69656711 0.13482225
#> [31] 0.92480952 0.42303395 0.41008485 0.98455234 0.94718689 0.18269195
#> [37] 0.94161997 0.68111627 0.39631325 0.89011782 0.62496016 0.78253826
#> [43] 0.42303395 0.74866091 0.83499215 0.59926944 0.64152748 0.35144548
#> [49] 0.82206109 0.65750047 0.74129307 0.95812103 0.95268697 0.71176190
#> [55] 0.75587798 0.06065349 0.06065349 0.68885196 0.32063478 0.55499293
#> [61] 0.63325747 0.91346206 0.86624941 0.48580245 0.96351829 0.84137234
#> [67] 0.75587798 0.51707059 0.50680308 0.48580245 0.86624941 0.56407133
#> [73] 0.25641618 0.78927161 0.53688825 0.32063478 0.52700710 0.27394319
#> [79] 0.90185884 0.87822886 0.58193416 0.67330173 0.42303395 0.80264975
#> [85] 0.58193416 0.22181272 0.84774451 0.42303395 0.20310722 0.27394319
#> [91] 0.98974916 0.82853224 0.42303395 0.86012399 0.92480952 0.66544760
#> [97] 0.93602692 0.61646455 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000
#>
#> $Time
#> 175 99 136 49 177 77 100 169 57 113 42 57.1 18
#> 21.91 21.19 21.83 12.19 12.53 7.27 16.07 22.41 14.46 22.86 12.43 14.46 15.21
#> 123 100.1 110 86 188 26 18.1 179 96 158 91 58 149
#> 13.00 16.07 17.56 23.81 16.16 15.77 15.21 18.63 14.54 20.14 5.33 19.34 8.37
#> 77.1 56 5 86.1 159 36 153 25 145 129 61 181 139
#> 7.27 12.21 16.43 23.81 10.55 21.19 21.33 6.32 10.07 23.41 10.12 16.46 21.49
#> 37 134 157 99.1 29 60 179.1 110.1 175.1 13 111 6 16
#> 12.52 17.81 15.10 21.19 15.45 13.15 18.63 17.56 21.91 14.34 17.45 15.64 8.71
#> 183 100.2 18.2 24 24.1 85 66 166 184 49.1 154 90 149.1
#> 9.24 16.07 15.21 23.89 23.89 16.44 22.13 19.98 17.77 12.19 12.63 20.94 8.37
#> 155 18.3 190 32 90.1 154.1 58.1 15 133 158.1 66.1 68 169.1
#> 13.08 15.21 20.81 20.90 20.94 12.63 19.34 22.68 14.65 20.14 22.13 20.62 22.41
#> 56.1 177.1 76 23 36.1 57.2 76.1 113.1 123.1 99.2 92 169.2 91.1
#> 12.21 12.53 19.22 16.92 21.19 14.46 19.22 22.86 13.00 21.19 22.92 22.41 5.33
#> 81 36.2 140 159.1 45 52 51 191 104 137 20 152 132
#> 14.06 21.19 12.68 10.55 17.42 10.42 18.23 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.1 142 109 109.1 28 31 3 65 47 83 22 146 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 165 75 38 62 46 165.1 121 156 48 121.1 191.1 191.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.1 71 19 28.1 135 173 120 161 9 2 20.1 160 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 131 104.2 163 80 21 67 132.1 47.1 126 152.2 143 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 198 186 53 3.1 34 94 138 83.2 7 120.1 80.1 198.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 48.1 196 64 3.2 116 31.1 138.1 146.1 7.1 17 94.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[25]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0009556918 0.9781421965 0.3781488569
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.87250427 0.01982772 0.10008055
#> grade_iii, Cure model
#> 0.43863102
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 175 21.91 1 43 0 0
#> 105 19.75 1 60 0 0
#> 175.1 21.91 1 43 0 0
#> 169 22.41 1 46 0 0
#> 92 22.92 1 47 0 1
#> 153 21.33 1 55 1 0
#> 42 12.43 1 49 0 1
#> 194 22.40 1 38 0 1
#> 23 16.92 1 61 0 0
#> 58 19.34 1 39 0 0
#> 30 17.43 1 78 0 0
#> 192 16.44 1 31 1 0
#> 127 3.53 1 62 0 1
#> 55 19.34 1 69 0 1
#> 168 23.72 1 70 0 0
#> 145 10.07 1 65 1 0
#> 32 20.90 1 37 1 0
#> 101 9.97 1 10 0 1
#> 140 12.68 1 59 1 0
#> 166 19.98 1 48 0 0
#> 10 10.53 1 34 0 0
#> 183 9.24 1 67 1 0
#> 40 18.00 1 28 1 0
#> 149 8.37 1 33 1 0
#> 77 7.27 1 67 0 1
#> 111 17.45 1 47 0 1
#> 69 23.23 1 25 0 1
#> 10.1 10.53 1 34 0 0
#> 45 17.42 1 54 0 1
#> 190 20.81 1 42 1 0
#> 106 16.67 1 49 1 0
#> 179 18.63 1 42 0 0
#> 158 20.14 1 74 1 0
#> 10.2 10.53 1 34 0 0
#> 123 13.00 1 44 1 0
#> 16 8.71 1 71 0 1
#> 189 10.51 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 93 10.33 1 52 0 1
#> 129 23.41 1 53 1 0
#> 76 19.22 1 54 0 1
#> 128 20.35 1 35 0 1
#> 181 16.46 1 45 0 1
#> 150 20.33 1 48 0 0
#> 79 16.23 1 54 1 0
#> 158.1 20.14 1 74 1 0
#> 88 18.37 1 47 0 0
#> 69.1 23.23 1 25 0 1
#> 136 21.83 1 43 0 1
#> 43 12.10 1 61 0 1
#> 145.1 10.07 1 65 1 0
#> 55.1 19.34 1 69 0 1
#> 70 7.38 1 30 1 0
#> 164 23.60 1 76 0 1
#> 55.2 19.34 1 69 0 1
#> 124 9.73 1 NA 1 0
#> 164.1 23.60 1 76 0 1
#> 183.1 9.24 1 67 1 0
#> 50 10.02 1 NA 1 0
#> 45.1 17.42 1 54 0 1
#> 10.3 10.53 1 34 0 0
#> 52 10.42 1 52 0 1
#> 24 23.89 1 38 0 0
#> 157 15.10 1 47 0 0
#> 66 22.13 1 53 0 0
#> 43.1 12.10 1 61 0 1
#> 25 6.32 1 34 1 0
#> 154 12.63 1 20 1 0
#> 18 15.21 1 49 1 0
#> 30.1 17.43 1 78 0 0
#> 107 11.18 1 54 1 0
#> 32.1 20.90 1 37 1 0
#> 37 12.52 1 57 1 0
#> 29 15.45 1 68 1 0
#> 30.2 17.43 1 78 0 0
#> 24.1 23.89 1 38 0 0
#> 164.2 23.60 1 76 0 1
#> 36 21.19 1 48 0 1
#> 128.1 20.35 1 35 0 1
#> 16.1 8.71 1 71 0 1
#> 145.2 10.07 1 65 1 0
#> 24.2 23.89 1 38 0 0
#> 108 18.29 1 39 0 1
#> 5 16.43 1 51 0 1
#> 81 14.06 1 34 0 0
#> 183.2 9.24 1 67 1 0
#> 128.2 20.35 1 35 0 1
#> 197 21.60 1 69 1 0
#> 79.1 16.23 1 54 1 0
#> 24.3 23.89 1 38 0 0
#> 145.3 10.07 1 65 1 0
#> 184 17.77 1 38 0 0
#> 110 17.56 1 65 0 1
#> 60 13.15 1 38 1 0
#> 187 9.92 1 39 1 0
#> 128.3 20.35 1 35 0 1
#> 177 12.53 1 75 0 0
#> 150.1 20.33 1 48 0 0
#> 8 18.43 1 32 0 0
#> 110.1 17.56 1 65 0 1
#> 188 16.16 1 46 0 1
#> 114 13.68 1 NA 0 0
#> 88.1 18.37 1 47 0 0
#> 25.1 6.32 1 34 1 0
#> 56 12.21 1 60 0 0
#> 8.1 18.43 1 32 0 0
#> 107.1 11.18 1 54 1 0
#> 106.1 16.67 1 49 1 0
#> 18.1 15.21 1 49 1 0
#> 155 13.08 1 26 0 0
#> 6 15.64 1 39 0 0
#> 168.1 23.72 1 70 0 0
#> 44 24.00 0 56 0 0
#> 152 24.00 0 36 0 1
#> 48 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 135 24.00 0 58 1 0
#> 138 24.00 0 44 1 0
#> 48.1 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 186 24.00 0 45 1 0
#> 162 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 64 24.00 0 43 0 0
#> 35 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 119 24.00 0 17 0 0
#> 115 24.00 0 NA 1 0
#> 143 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 47 24.00 0 38 0 1
#> 82 24.00 0 34 0 0
#> 2 24.00 0 9 0 0
#> 152.1 24.00 0 36 0 1
#> 3 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 27 24.00 0 63 1 0
#> 144 24.00 0 28 0 1
#> 65 24.00 0 57 1 0
#> 132 24.00 0 55 0 0
#> 31 24.00 0 36 0 1
#> 67 24.00 0 25 0 0
#> 95 24.00 0 68 0 1
#> 31.1 24.00 0 36 0 1
#> 196 24.00 0 19 0 0
#> 198 24.00 0 66 0 1
#> 73 24.00 0 NA 0 1
#> 38 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 94 24.00 0 51 0 1
#> 87 24.00 0 27 0 0
#> 27.1 24.00 0 63 1 0
#> 95.1 24.00 0 68 0 1
#> 7 24.00 0 37 1 0
#> 163 24.00 0 66 0 0
#> 67.1 24.00 0 25 0 0
#> 98.1 24.00 0 34 1 0
#> 65.1 24.00 0 57 1 0
#> 156 24.00 0 50 1 0
#> 144.1 24.00 0 28 0 1
#> 47.1 24.00 0 38 0 1
#> 122.1 24.00 0 66 0 0
#> 11 24.00 0 42 0 1
#> 35.1 24.00 0 51 0 0
#> 44.1 24.00 0 56 0 0
#> 162.1 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 151 24.00 0 42 0 0
#> 73.1 24.00 0 NA 0 1
#> 172 24.00 0 41 0 0
#> 200 24.00 0 64 0 0
#> 80 24.00 0 41 0 0
#> 135.1 24.00 0 58 1 0
#> 174 24.00 0 49 1 0
#> 152.2 24.00 0 36 0 1
#> 74.1 24.00 0 43 0 1
#> 143.1 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 120 24.00 0 68 0 1
#> 102 24.00 0 49 0 0
#> 142 24.00 0 53 0 0
#> 21 24.00 0 47 0 0
#> 28 24.00 0 67 1 0
#> 137.1 24.00 0 45 1 0
#> 174.1 24.00 0 49 1 0
#> 119.1 24.00 0 17 0 0
#> 47.2 24.00 0 38 0 1
#> 161 24.00 0 45 0 0
#> 185 24.00 0 44 1 0
#> 178 24.00 0 52 1 0
#> 112 24.00 0 61 0 0
#> 9.1 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 132.1 24.00 0 55 0 0
#> 146 24.00 0 63 1 0
#> 1 24.00 0 23 1 0
#> 191 24.00 0 60 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.873 NA NA NA
#> 2 age, Cure model 0.0198 NA NA NA
#> 3 grade_ii, Cure model 0.100 NA NA NA
#> 4 grade_iii, Cure model 0.439 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000956 NA NA NA
#> 2 grade_ii, Survival model 0.978 NA NA NA
#> 3 grade_iii, Survival model 0.378 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.87250 0.01983 0.10008 0.43863
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 259 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.87250427 0.01982772 0.10008055 0.43863102
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0009556918 0.9781421965 0.3781488569
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.31704329 0.50395476 0.31704329 0.27611435 0.26220799 0.36890574
#> [7] 0.83573169 0.28998946 0.68402299 0.51272469 0.64484002 0.71436123
#> [13] 0.99484350 0.51272469 0.12997880 0.90798528 0.39198657 0.93047512
#> [19] 0.81046909 0.49517582 0.87234878 0.94173118 0.60459943 0.96864197
#> [25] 0.97925994 0.63686201 0.23437719 0.87234878 0.66841241 0.41247884
#> [31] 0.69186792 0.55440161 0.47775923 0.87234878 0.80397360 0.95790020
#> [37] 0.10719921 0.90203771 0.21909854 0.54596527 0.42241356 0.70686457
#> [43] 0.45908012 0.72904598 0.47775923 0.57955319 0.23437719 0.34339920
#> [49] 0.84813677 0.90798528 0.51272469 0.97397608 0.17076485 0.51272469
#> [55] 0.17076485 0.94173118 0.66841241 0.87234878 0.89606913 0.04086826
#> [61] 0.77741188 0.30353199 0.84813677 0.98452798 0.81687151 0.76408185
#> [67] 0.64484002 0.86039608 0.39198657 0.82950332 0.75717111 0.64484002
#> [73] 0.04086826 0.17076485 0.38053854 0.42241356 0.95790020 0.90798528
#> [79] 0.04086826 0.59625157 0.72172349 0.78410307 0.94173118 0.42241356
#> [85] 0.35657177 0.72904598 0.04086826 0.90798528 0.61275236 0.62090128
#> [91] 0.79079238 0.93613293 0.42241356 0.82318921 0.45908012 0.56283270
#> [97] 0.62090128 0.74311131 0.57955319 0.98452798 0.84193558 0.56283270
#> [103] 0.86039608 0.69186792 0.76408185 0.79738367 0.75014246 0.12997880
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 175 105 175.1 169 92 153 42 194 23 58 30 192 127
#> 21.91 19.75 21.91 22.41 22.92 21.33 12.43 22.40 16.92 19.34 17.43 16.44 3.53
#> 55 168 145 32 101 140 166 10 183 40 149 77 111
#> 19.34 23.72 10.07 20.90 9.97 12.68 19.98 10.53 9.24 18.00 8.37 7.27 17.45
#> 69 10.1 45 190 106 179 158 10.2 123 16 78 93 129
#> 23.23 10.53 17.42 20.81 16.67 18.63 20.14 10.53 13.00 8.71 23.88 10.33 23.41
#> 76 128 181 150 79 158.1 88 69.1 136 43 145.1 55.1 70
#> 19.22 20.35 16.46 20.33 16.23 20.14 18.37 23.23 21.83 12.10 10.07 19.34 7.38
#> 164 55.2 164.1 183.1 45.1 10.3 52 24 157 66 43.1 25 154
#> 23.60 19.34 23.60 9.24 17.42 10.53 10.42 23.89 15.10 22.13 12.10 6.32 12.63
#> 18 30.1 107 32.1 37 29 30.2 24.1 164.2 36 128.1 16.1 145.2
#> 15.21 17.43 11.18 20.90 12.52 15.45 17.43 23.89 23.60 21.19 20.35 8.71 10.07
#> 24.2 108 5 81 183.2 128.2 197 79.1 24.3 145.3 184 110 60
#> 23.89 18.29 16.43 14.06 9.24 20.35 21.60 16.23 23.89 10.07 17.77 17.56 13.15
#> 187 128.3 177 150.1 8 110.1 188 88.1 25.1 56 8.1 107.1 106.1
#> 9.92 20.35 12.53 20.33 18.43 17.56 16.16 18.37 6.32 12.21 18.43 11.18 16.67
#> 18.1 155 6 168.1 44 152 48 9 19 135 138 48.1 137
#> 15.21 13.08 15.64 23.72 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 162 17 64 35 122 62 119 143 98 47 82 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.1 3 165 27 144 65 132 31 67 95 31.1 196 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 74 94 87 27.1 95.1 7 163 67.1 98.1 65.1 156 144.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.1 122.1 11 35.1 44.1 162.1 160 46 151 172 200 80 135.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 152.2 74.1 143.1 103 120 102 142 21 28 137.1 174.1 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.2 161 185 178 112 9.1 104 132.1 146 1 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[26]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.018311400 -0.028311331 0.003060547
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.92071813 0.01518074 0.01436094
#> grade_iii, Cure model
#> 1.43661207
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 15 22.68 1 48 0 0
#> 153 21.33 1 55 1 0
#> 153.1 21.33 1 55 1 0
#> 188 16.16 1 46 0 1
#> 171 16.57 1 41 0 1
#> 81 14.06 1 34 0 0
#> 52 10.42 1 52 0 1
#> 43 12.10 1 61 0 1
#> 45 17.42 1 54 0 1
#> 187 9.92 1 39 1 0
#> 171.1 16.57 1 41 0 1
#> 36 21.19 1 48 0 1
#> 149 8.37 1 33 1 0
#> 170 19.54 1 43 0 1
#> 13 14.34 1 54 0 1
#> 195 11.76 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 100 16.07 1 60 0 0
#> 190 20.81 1 42 1 0
#> 15.1 22.68 1 48 0 0
#> 114 13.68 1 NA 0 0
#> 18 15.21 1 49 1 0
#> 51 18.23 1 83 0 1
#> 41 18.02 1 40 1 0
#> 39 15.59 1 37 0 1
#> 24 23.89 1 38 0 0
#> 92 22.92 1 47 0 1
#> 145 10.07 1 65 1 0
#> 195.1 11.76 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 199 19.81 1 NA 0 1
#> 10 10.53 1 34 0 0
#> 5 16.43 1 51 0 1
#> 183 9.24 1 67 1 0
#> 167 15.55 1 56 1 0
#> 99 21.19 1 38 0 1
#> 77 7.27 1 67 0 1
#> 57 14.46 1 45 0 1
#> 6 15.64 1 39 0 0
#> 180 14.82 1 37 0 0
#> 43.1 12.10 1 61 0 1
#> 6.1 15.64 1 39 0 0
#> 99.1 21.19 1 38 0 1
#> 63 22.77 1 31 1 0
#> 92.1 22.92 1 47 0 1
#> 110 17.56 1 65 0 1
#> 4 17.64 1 NA 0 1
#> 14 12.89 1 21 0 0
#> 10.1 10.53 1 34 0 0
#> 85 16.44 1 36 0 0
#> 190.1 20.81 1 42 1 0
#> 184 17.77 1 38 0 0
#> 6.2 15.64 1 39 0 0
#> 43.2 12.10 1 61 0 1
#> 107 11.18 1 54 1 0
#> 107.1 11.18 1 54 1 0
#> 180.1 14.82 1 37 0 0
#> 97 19.14 1 65 0 1
#> 56 12.21 1 60 0 0
#> 133 14.65 1 57 0 0
#> 190.2 20.81 1 42 1 0
#> 167.1 15.55 1 56 1 0
#> 166 19.98 1 48 0 0
#> 128 20.35 1 35 0 1
#> 99.2 21.19 1 38 0 1
#> 13.1 14.34 1 54 0 1
#> 157 15.10 1 47 0 0
#> 58 19.34 1 39 0 0
#> 93 10.33 1 52 0 1
#> 81.1 14.06 1 34 0 0
#> 155 13.08 1 26 0 0
#> 43.3 12.10 1 61 0 1
#> 189 10.51 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 175 21.91 1 43 0 0
#> 49 12.19 1 48 1 0
#> 69.1 23.23 1 25 0 1
#> 124 9.73 1 NA 1 0
#> 59 10.16 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 197 21.60 1 69 1 0
#> 150 20.33 1 48 0 0
#> 93.1 10.33 1 52 0 1
#> 99.3 21.19 1 38 0 1
#> 79 16.23 1 54 1 0
#> 96 14.54 1 33 0 1
#> 129 23.41 1 53 1 0
#> 8 18.43 1 32 0 0
#> 100.1 16.07 1 60 0 0
#> 110.1 17.56 1 65 0 1
#> 136 21.83 1 43 0 1
#> 155.1 13.08 1 26 0 0
#> 25 6.32 1 34 1 0
#> 51.1 18.23 1 83 0 1
#> 39.1 15.59 1 37 0 1
#> 128.1 20.35 1 35 0 1
#> 91 5.33 1 61 0 1
#> 6.3 15.64 1 39 0 0
#> 51.2 18.23 1 83 0 1
#> 105 19.75 1 60 0 0
#> 76 19.22 1 54 0 1
#> 24.1 23.89 1 38 0 0
#> 192 16.44 1 31 1 0
#> 177 12.53 1 75 0 0
#> 113 22.86 1 34 0 0
#> 100.2 16.07 1 60 0 0
#> 139 21.49 1 63 1 0
#> 90 20.94 1 50 0 1
#> 128.2 20.35 1 35 0 1
#> 175.1 21.91 1 43 0 0
#> 89 11.44 1 NA 0 0
#> 77.1 7.27 1 67 0 1
#> 137 24.00 0 45 1 0
#> 48 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 54 24.00 0 53 1 0
#> 74 24.00 0 43 0 1
#> 174 24.00 0 49 1 0
#> 137.1 24.00 0 45 1 0
#> 178 24.00 0 52 1 0
#> 33 24.00 0 53 0 0
#> 80 24.00 0 41 0 0
#> 48.1 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 185 24.00 0 44 1 0
#> 83 24.00 0 6 0 0
#> 80.1 24.00 0 41 0 0
#> 80.2 24.00 0 41 0 0
#> 162 24.00 0 51 0 0
#> 71 24.00 0 51 0 0
#> 74.1 24.00 0 43 0 1
#> 19 24.00 0 57 0 1
#> 102 24.00 0 49 0 0
#> 72 24.00 0 40 0 1
#> 162.1 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 173 24.00 0 19 0 1
#> 44 24.00 0 56 0 0
#> 109 24.00 0 48 0 0
#> 73 24.00 0 NA 0 1
#> 3 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 178.1 24.00 0 52 1 0
#> 47 24.00 0 38 0 1
#> 2 24.00 0 9 0 0
#> 147 24.00 0 76 1 0
#> 112 24.00 0 61 0 0
#> 147.1 24.00 0 76 1 0
#> 196 24.00 0 19 0 0
#> 3.1 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 2.1 24.00 0 9 0 0
#> 75 24.00 0 21 1 0
#> 94 24.00 0 51 0 1
#> 62 24.00 0 71 0 0
#> 87 24.00 0 27 0 0
#> 147.2 24.00 0 76 1 0
#> 62.1 24.00 0 71 0 0
#> 143 24.00 0 51 0 0
#> 2.2 24.00 0 9 0 0
#> 104 24.00 0 50 1 0
#> 35 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 122 24.00 0 66 0 0
#> 72.1 24.00 0 40 0 1
#> 44.1 24.00 0 56 0 0
#> 12 24.00 0 63 0 0
#> 19.1 24.00 0 57 0 1
#> 44.2 24.00 0 56 0 0
#> 151 24.00 0 42 0 0
#> 62.2 24.00 0 71 0 0
#> 182 24.00 0 35 0 0
#> 115 24.00 0 NA 1 0
#> 156 24.00 0 50 1 0
#> 176 24.00 0 43 0 1
#> 80.3 24.00 0 41 0 0
#> 87.1 24.00 0 27 0 0
#> 109.1 24.00 0 48 0 0
#> 44.3 24.00 0 56 0 0
#> 165 24.00 0 47 0 0
#> 47.1 24.00 0 38 0 1
#> 196.1 24.00 0 19 0 0
#> 126 24.00 0 48 0 0
#> 38 24.00 0 31 1 0
#> 137.2 24.00 0 45 1 0
#> 1.1 24.00 0 23 1 0
#> 21 24.00 0 47 0 0
#> 22.1 24.00 0 52 1 0
#> 137.3 24.00 0 45 1 0
#> 143.1 24.00 0 51 0 0
#> 186 24.00 0 45 1 0
#> 7 24.00 0 37 1 0
#> 48.2 24.00 0 31 1 0
#> 102.1 24.00 0 49 0 0
#> 126.1 24.00 0 48 0 0
#> 196.2 24.00 0 19 0 0
#> 143.2 24.00 0 51 0 0
#> 172.1 24.00 0 41 0 0
#> 102.2 24.00 0 49 0 0
#> 28 24.00 0 67 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.921 NA NA NA
#> 2 age, Cure model 0.0152 NA NA NA
#> 3 grade_ii, Cure model 0.0144 NA NA NA
#> 4 grade_iii, Cure model 1.44 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0183 NA NA NA
#> 2 grade_ii, Survival model -0.0283 NA NA NA
#> 3 grade_iii, Survival model 0.00306 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.92072 0.01518 0.01436 1.43661
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 239.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.92071813 0.01518074 0.01436094 1.43661207
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.018311400 -0.028311331 0.003060547
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.3585300 0.4755705 0.4755705 0.7635477 0.7272333 0.8784951 0.9508436
#> [8] 0.9161102 0.7209502 0.9676938 0.7272333 0.4980306 0.9759618 0.6353287
#> [15] 0.8688697 0.7861242 0.7694150 0.5563258 0.3585300 0.8337534 0.6747265
#> [22] 0.6948814 0.8128762 0.1181085 0.2779691 0.9635217 0.2264043 0.9422564
#> [29] 0.7516164 0.9718481 0.8234280 0.4980306 0.9800620 0.8639509 0.7916427
#> [36] 0.8439802 0.9161102 0.7916427 0.4980306 0.3392274 0.2779691 0.7082519
#> [43] 0.8975035 0.9422564 0.7395077 0.5563258 0.7015987 0.7916427 0.9161102
#> [50] 0.9336010 0.9336010 0.8439802 0.6594377 0.9069061 0.8540167 0.5563258
#> [57] 0.8234280 0.6185219 0.5836356 0.4980306 0.8688697 0.8388881 0.6434912
#> [64] 0.9551160 0.8784951 0.8880303 0.9161102 0.3912711 0.4073059 0.9115237
#> [71] 0.2264043 0.9960610 0.4501534 0.6098375 0.9551160 0.4980306 0.7576199
#> [78] 0.8589958 0.1944670 0.6671170 0.7694150 0.7082519 0.4360862 0.8880303
#> [85] 0.9880831 0.6747265 0.8128762 0.5836356 0.9920886 0.7916427 0.6747265
#> [92] 0.6270379 0.6515472 0.1181085 0.7395077 0.9022409 0.3191070 0.7694150
#> [99] 0.4632244 0.5465329 0.5836356 0.4073059 0.9800620 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 15 153 153.1 188 171 81 52 43 45 187 171.1 36 149
#> 22.68 21.33 21.33 16.16 16.57 14.06 10.42 12.10 17.42 9.92 16.57 21.19 8.37
#> 170 13 125 100 190 15.1 18 51 41 39 24 92 145
#> 19.54 14.34 15.65 16.07 20.81 22.68 15.21 18.23 18.02 15.59 23.89 22.92 10.07
#> 69 10 5 183 167 99 77 57 6 180 43.1 6.1 99.1
#> 23.23 10.53 16.43 9.24 15.55 21.19 7.27 14.46 15.64 14.82 12.10 15.64 21.19
#> 63 92.1 110 14 10.1 85 190.1 184 6.2 43.2 107 107.1 180.1
#> 22.77 22.92 17.56 12.89 10.53 16.44 20.81 17.77 15.64 12.10 11.18 11.18 14.82
#> 97 56 133 190.2 167.1 166 128 99.2 13.1 157 58 93 81.1
#> 19.14 12.21 14.65 20.81 15.55 19.98 20.35 21.19 14.34 15.10 19.34 10.33 14.06
#> 155 43.3 194 175 49 69.1 127 197 150 93.1 99.3 79 96
#> 13.08 12.10 22.40 21.91 12.19 23.23 3.53 21.60 20.33 10.33 21.19 16.23 14.54
#> 129 8 100.1 110.1 136 155.1 25 51.1 39.1 128.1 91 6.3 51.2
#> 23.41 18.43 16.07 17.56 21.83 13.08 6.32 18.23 15.59 20.35 5.33 15.64 18.23
#> 105 76 24.1 192 177 113 100.2 139 90 128.2 175.1 77.1 137
#> 19.75 19.22 23.89 16.44 12.53 22.86 16.07 21.49 20.94 20.35 21.91 7.27 24.00
#> 48 172 54 74 174 137.1 178 33 80 48.1 98 185 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80.1 80.2 162 71 74.1 19 102 72 162.1 152 173 44 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 1 178.1 47 2 147 112 147.1 196 3.1 11 2.1 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 62 87 147.2 62.1 143 2.2 104 35 22 122 72.1 44.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 19.1 44.2 151 62.2 182 156 176 80.3 87.1 109.1 44.3 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.1 196.1 126 38 137.2 1.1 21 22.1 137.3 143.1 186 7 48.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.1 126.1 196.2 143.2 172.1 102.2 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[27]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009172204 0.495272835 -0.010182932
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.96741508 0.01789457 0.26060859
#> grade_iii, Cure model
#> 0.89635661
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 60 13.15 1 38 1 0
#> 145 10.07 1 65 1 0
#> 197 21.60 1 69 1 0
#> 96 14.54 1 33 0 1
#> 123 13.00 1 44 1 0
#> 199 19.81 1 NA 0 1
#> 99 21.19 1 38 0 1
#> 55 19.34 1 69 0 1
#> 168 23.72 1 70 0 0
#> 39 15.59 1 37 0 1
#> 189 10.51 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 61 10.12 1 36 0 1
#> 153 21.33 1 55 1 0
#> 149 8.37 1 33 1 0
#> 69 23.23 1 25 0 1
#> 85 16.44 1 36 0 0
#> 56 12.21 1 60 0 0
#> 171 16.57 1 41 0 1
#> 57 14.46 1 45 0 1
#> 69.1 23.23 1 25 0 1
#> 100 16.07 1 60 0 0
#> 70 7.38 1 30 1 0
#> 117 17.46 1 26 0 1
#> 23 16.92 1 61 0 0
#> 96.1 14.54 1 33 0 1
#> 157 15.10 1 47 0 0
#> 157.1 15.10 1 47 0 0
#> 124 9.73 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 41 18.02 1 40 1 0
#> 168.1 23.72 1 70 0 0
#> 55.1 19.34 1 69 0 1
#> 154 12.63 1 20 1 0
#> 45 17.42 1 54 0 1
#> 195 11.76 1 NA 1 0
#> 69.2 23.23 1 25 0 1
#> 88 18.37 1 47 0 0
#> 69.3 23.23 1 25 0 1
#> 58 19.34 1 39 0 0
#> 117.1 17.46 1 26 0 1
#> 134 17.81 1 47 1 0
#> 36.1 21.19 1 48 0 1
#> 170 19.54 1 43 0 1
#> 79 16.23 1 54 1 0
#> 51 18.23 1 83 0 1
#> 23.1 16.92 1 61 0 0
#> 164 23.60 1 76 0 1
#> 129 23.41 1 53 1 0
#> 133 14.65 1 57 0 0
#> 43 12.10 1 61 0 1
#> 23.2 16.92 1 61 0 0
#> 18 15.21 1 49 1 0
#> 97 19.14 1 65 0 1
#> 6 15.64 1 39 0 0
#> 97.1 19.14 1 65 0 1
#> 183 9.24 1 67 1 0
#> 192 16.44 1 31 1 0
#> 15 22.68 1 48 0 0
#> 139 21.49 1 63 1 0
#> 179 18.63 1 42 0 0
#> 114 13.68 1 NA 0 0
#> 194 22.40 1 38 0 1
#> 139.1 21.49 1 63 1 0
#> 153.1 21.33 1 55 1 0
#> 42 12.43 1 49 0 1
#> 25 6.32 1 34 1 0
#> 149.1 8.37 1 33 1 0
#> 192.1 16.44 1 31 1 0
#> 14 12.89 1 21 0 0
#> 56.1 12.21 1 60 0 0
#> 43.1 12.10 1 61 0 1
#> 166 19.98 1 48 0 0
#> 61.1 10.12 1 36 0 1
#> 153.2 21.33 1 55 1 0
#> 166.1 19.98 1 48 0 0
#> 76.1 19.22 1 54 0 1
#> 96.2 14.54 1 33 0 1
#> 49 12.19 1 48 1 0
#> 117.2 17.46 1 26 0 1
#> 169 22.41 1 46 0 0
#> 192.2 16.44 1 31 1 0
#> 56.2 12.21 1 60 0 0
#> 88.1 18.37 1 47 0 0
#> 145.1 10.07 1 65 1 0
#> 30 17.43 1 78 0 0
#> 194.1 22.40 1 38 0 1
#> 125 15.65 1 67 1 0
#> 93 10.33 1 52 0 1
#> 78 23.88 1 43 0 0
#> 43.2 12.10 1 61 0 1
#> 30.1 17.43 1 78 0 0
#> 76.2 19.22 1 54 0 1
#> 110 17.56 1 65 0 1
#> 170.1 19.54 1 43 0 1
#> 175 21.91 1 43 0 0
#> 168.2 23.72 1 70 0 0
#> 157.2 15.10 1 47 0 0
#> 90 20.94 1 50 0 1
#> 114.1 13.68 1 NA 0 0
#> 32 20.90 1 37 1 0
#> 86 23.81 1 58 0 1
#> 133.1 14.65 1 57 0 0
#> 13 14.34 1 54 0 1
#> 192.3 16.44 1 31 1 0
#> 149.2 8.37 1 33 1 0
#> 184 17.77 1 38 0 0
#> 187 9.92 1 39 1 0
#> 197.1 21.60 1 69 1 0
#> 32.1 20.90 1 37 1 0
#> 29 15.45 1 68 1 0
#> 136 21.83 1 43 0 1
#> 120 24.00 0 68 0 1
#> 12 24.00 0 63 0 0
#> 191 24.00 0 60 0 1
#> 9 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 87 24.00 0 27 0 0
#> 11 24.00 0 42 0 1
#> 46 24.00 0 71 0 0
#> 47 24.00 0 38 0 1
#> 173 24.00 0 19 0 1
#> 98 24.00 0 34 1 0
#> 72 24.00 0 40 0 1
#> 132 24.00 0 55 0 0
#> 20 24.00 0 46 1 0
#> 131 24.00 0 66 0 0
#> 87.1 24.00 0 27 0 0
#> 142 24.00 0 53 0 0
#> 116 24.00 0 58 0 1
#> 7 24.00 0 37 1 0
#> 185 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 143 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#> 163 24.00 0 66 0 0
#> 186 24.00 0 45 1 0
#> 22 24.00 0 52 1 0
#> 161 24.00 0 45 0 0
#> 7.1 24.00 0 37 1 0
#> 31 24.00 0 36 0 1
#> 31.1 24.00 0 36 0 1
#> 160 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 142.1 24.00 0 53 0 0
#> 65 24.00 0 57 1 0
#> 48 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 196 24.00 0 19 0 0
#> 3 24.00 0 31 1 0
#> 132.1 24.00 0 55 0 0
#> 176.1 24.00 0 43 0 1
#> 142.2 24.00 0 53 0 0
#> 3.1 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 115 24.00 0 NA 1 0
#> 34 24.00 0 36 0 0
#> 34.1 24.00 0 36 0 0
#> 141 24.00 0 44 1 0
#> 185.1 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 17 24.00 0 38 0 1
#> 46.1 24.00 0 71 0 0
#> 119 24.00 0 17 0 0
#> 75 24.00 0 21 1 0
#> 186.1 24.00 0 45 1 0
#> 73 24.00 0 NA 0 1
#> 34.2 24.00 0 36 0 0
#> 172 24.00 0 41 0 0
#> 104 24.00 0 50 1 0
#> 46.2 24.00 0 71 0 0
#> 1 24.00 0 23 1 0
#> 2 24.00 0 9 0 0
#> 173.1 24.00 0 19 0 1
#> 53 24.00 0 32 0 1
#> 115.1 24.00 0 NA 1 0
#> 47.1 24.00 0 38 0 1
#> 54 24.00 0 53 1 0
#> 178 24.00 0 52 1 0
#> 131.1 24.00 0 66 0 0
#> 95.1 24.00 0 68 0 1
#> 137 24.00 0 45 1 0
#> 75.1 24.00 0 21 1 0
#> 33 24.00 0 53 0 0
#> 182 24.00 0 35 0 0
#> 80 24.00 0 41 0 0
#> 95.2 24.00 0 68 0 1
#> 132.2 24.00 0 55 0 0
#> 33.1 24.00 0 53 0 0
#> 115.2 24.00 0 NA 1 0
#> 121 24.00 0 57 1 0
#> 138 24.00 0 44 1 0
#> 161.1 24.00 0 45 0 0
#> 12.1 24.00 0 63 0 0
#> 104.1 24.00 0 50 1 0
#> 72.1 24.00 0 40 0 1
#> 163.1 24.00 0 66 0 0
#> 74 24.00 0 43 0 1
#> 73.1 24.00 0 NA 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.967 NA NA NA
#> 2 age, Cure model 0.0179 NA NA NA
#> 3 grade_ii, Cure model 0.261 NA NA NA
#> 4 grade_iii, Cure model 0.896 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00917 NA NA NA
#> 2 grade_ii, Survival model 0.495 NA NA NA
#> 3 grade_iii, Survival model -0.0102 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.96742 0.01789 0.26061 0.89636
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 259.2
#> Residual Deviance: 250.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.96741508 0.01789457 0.26060859 0.89635661
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009172204 0.495272835 -0.010182932
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.7131530960 0.8906930649 0.0897563799 0.6558219390 0.7248058618
#> [6] 0.1406380071 0.2194997796 0.0058170033 0.5670996361 0.2449085999
#> [11] 0.8663382841 0.1191347839 0.9396656834 0.0285155092 0.4720210853
#> [16] 0.7713752327 0.4610444555 0.6898639372 0.0285155092 0.5344241563
#> [21] 0.9757473742 0.3680894517 0.4291299717 0.6558219390 0.6001571314
#> [26] 0.6001571314 0.1406380071 0.3284818174 0.0058170033 0.2194997796
#> [31] 0.7481077734 0.4185624555 0.0285155092 0.2994509563 0.0285155092
#> [36] 0.2194997796 0.3680894517 0.3383252215 0.1406380071 0.2030277203
#> [41] 0.5236625337 0.3185978640 0.4291299717 0.0167648801 0.0226427708
#> [46] 0.6332441345 0.8183900174 0.4291299717 0.5891359755 0.2714099212
#> [51] 0.5561567764 0.2714099212 0.9273796944 0.4720210853 0.0486614089
#> [56] 0.1043620678 0.2899361396 0.0616672987 0.1043620678 0.1191347839
#> [61] 0.7597086798 0.9878886689 0.9396656834 0.4720210853 0.7364406690
#> [66] 0.7713752327 0.8183900174 0.1869891124 0.8663382841 0.1191347839
#> [71] 0.1869891124 0.2449085999 0.6558219390 0.8065129904 0.3680894517
#> [76] 0.0550318621 0.4720210853 0.7713752327 0.2994509563 0.8906930649
#> [81] 0.3978985974 0.0616672987 0.5452782905 0.8541734719 0.0005950146
#> [86] 0.8183900174 0.3978985974 0.2449085999 0.3580564635 0.2030277203
#> [91] 0.0750528705 0.0058170033 0.6001571314 0.1633335892 0.1714264063
#> [96] 0.0026230336 0.6332441345 0.7014701658 0.4720210853 0.9396656834
#> [101] 0.3481497008 0.9151119796 0.0897563799 0.1714264063 0.5781051474
#> [106] 0.0822952355 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 60 145 197 96 123 99 55 168 39 76 61 153 149
#> 13.15 10.07 21.60 14.54 13.00 21.19 19.34 23.72 15.59 19.22 10.12 21.33 8.37
#> 69 85 56 171 57 69.1 100 70 117 23 96.1 157 157.1
#> 23.23 16.44 12.21 16.57 14.46 23.23 16.07 7.38 17.46 16.92 14.54 15.10 15.10
#> 36 41 168.1 55.1 154 45 69.2 88 69.3 58 117.1 134 36.1
#> 21.19 18.02 23.72 19.34 12.63 17.42 23.23 18.37 23.23 19.34 17.46 17.81 21.19
#> 170 79 51 23.1 164 129 133 43 23.2 18 97 6 97.1
#> 19.54 16.23 18.23 16.92 23.60 23.41 14.65 12.10 16.92 15.21 19.14 15.64 19.14
#> 183 192 15 139 179 194 139.1 153.1 42 25 149.1 192.1 14
#> 9.24 16.44 22.68 21.49 18.63 22.40 21.49 21.33 12.43 6.32 8.37 16.44 12.89
#> 56.1 43.1 166 61.1 153.2 166.1 76.1 96.2 49 117.2 169 192.2 56.2
#> 12.21 12.10 19.98 10.12 21.33 19.98 19.22 14.54 12.19 17.46 22.41 16.44 12.21
#> 88.1 145.1 30 194.1 125 93 78 43.2 30.1 76.2 110 170.1 175
#> 18.37 10.07 17.43 22.40 15.65 10.33 23.88 12.10 17.43 19.22 17.56 19.54 21.91
#> 168.2 157.2 90 32 86 133.1 13 192.3 149.2 184 187 197.1 32.1
#> 23.72 15.10 20.94 20.90 23.81 14.65 14.34 16.44 8.37 17.77 9.92 21.60 20.90
#> 29 136 120 12 191 9 44 87 11 46 47 173 98
#> 15.45 21.83 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 132 20 131 87.1 142 116 7 185 118 148 143 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 186 22 161 7.1 31 31.1 160 103 142.1 65 48 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 3 132.1 176.1 142.2 3.1 135 34 34.1 141 185.1 21 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.1 119 75 186.1 34.2 172 104 46.2 1 2 173.1 53 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 178 131.1 95.1 137 75.1 33 182 80 95.2 132.2 33.1 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 161.1 12.1 104.1 72.1 163.1 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[28]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00474172 0.99349664 0.25872243
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.2209444 0.0271000 -0.2303001
#> grade_iii, Cure model
#> 0.5423489
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 180 14.82 1 37 0 0
#> 170 19.54 1 43 0 1
#> 181 16.46 1 45 0 1
#> 99 21.19 1 38 0 1
#> 127 3.53 1 62 0 1
#> 78 23.88 1 43 0 0
#> 181.1 16.46 1 45 0 1
#> 88 18.37 1 47 0 0
#> 81 14.06 1 34 0 0
#> 57 14.46 1 45 0 1
#> 51 18.23 1 83 0 1
#> 150 20.33 1 48 0 0
#> 164 23.60 1 76 0 1
#> 136 21.83 1 43 0 1
#> 128 20.35 1 35 0 1
#> 90 20.94 1 50 0 1
#> 36 21.19 1 48 0 1
#> 170.1 19.54 1 43 0 1
#> 113 22.86 1 34 0 0
#> 100 16.07 1 60 0 0
#> 179 18.63 1 42 0 0
#> 4 17.64 1 NA 0 1
#> 18 15.21 1 49 1 0
#> 189 10.51 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 85 16.44 1 36 0 0
#> 63 22.77 1 31 1 0
#> 183 9.24 1 67 1 0
#> 139 21.49 1 63 1 0
#> 189.1 10.51 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 93 10.33 1 52 0 1
#> 25 6.32 1 34 1 0
#> 128.1 20.35 1 35 0 1
#> 164.1 23.60 1 76 0 1
#> 52 10.42 1 52 0 1
#> 169.1 22.41 1 46 0 0
#> 170.2 19.54 1 43 0 1
#> 111 17.45 1 47 0 1
#> 179.1 18.63 1 42 0 0
#> 130 16.47 1 53 0 1
#> 159 10.55 1 50 0 1
#> 92 22.92 1 47 0 1
#> 189.2 10.51 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 6 15.64 1 39 0 0
#> 29 15.45 1 68 1 0
#> 164.2 23.60 1 76 0 1
#> 180.1 14.82 1 37 0 0
#> 125 15.65 1 67 1 0
#> 145 10.07 1 65 1 0
#> 57.1 14.46 1 45 0 1
#> 136.1 21.83 1 43 0 1
#> 157 15.10 1 47 0 0
#> 168 23.72 1 70 0 0
#> 130.1 16.47 1 53 0 1
#> 66 22.13 1 53 0 0
#> 51.1 18.23 1 83 0 1
#> 100.1 16.07 1 60 0 0
#> 125.1 15.65 1 67 1 0
#> 187 9.92 1 39 1 0
#> 15 22.68 1 48 0 0
#> 45 17.42 1 54 0 1
#> 167 15.55 1 56 1 0
#> 114 13.68 1 NA 0 0
#> 78.1 23.88 1 43 0 0
#> 55 19.34 1 69 0 1
#> 58 19.34 1 39 0 0
#> 60 13.15 1 38 1 0
#> 177 12.53 1 75 0 0
#> 111.1 17.45 1 47 0 1
#> 168.1 23.72 1 70 0 0
#> 190 20.81 1 42 1 0
#> 32 20.90 1 37 1 0
#> 85.1 16.44 1 36 0 0
#> 99.1 21.19 1 38 0 1
#> 167.1 15.55 1 56 1 0
#> 158 20.14 1 74 1 0
#> 154 12.63 1 20 1 0
#> 128.2 20.35 1 35 0 1
#> 150.1 20.33 1 48 0 0
#> 123 13.00 1 44 1 0
#> 6.1 15.64 1 39 0 0
#> 180.2 14.82 1 37 0 0
#> 68 20.62 1 44 0 0
#> 29.1 15.45 1 68 1 0
#> 92.1 22.92 1 47 0 1
#> 145.1 10.07 1 65 1 0
#> 76 19.22 1 54 0 1
#> 136.2 21.83 1 43 0 1
#> 40 18.00 1 28 1 0
#> 177.1 12.53 1 75 0 0
#> 159.1 10.55 1 50 0 1
#> 154.1 12.63 1 20 1 0
#> 184 17.77 1 38 0 0
#> 183.1 9.24 1 67 1 0
#> 187.1 9.92 1 39 1 0
#> 154.2 12.63 1 20 1 0
#> 76.1 19.22 1 54 0 1
#> 150.2 20.33 1 48 0 0
#> 59 10.16 1 NA 1 0
#> 93.1 10.33 1 52 0 1
#> 29.2 15.45 1 68 1 0
#> 4.1 17.64 1 NA 0 1
#> 199 19.81 1 NA 0 1
#> 125.2 15.65 1 67 1 0
#> 168.2 23.72 1 70 0 0
#> 30 17.43 1 78 0 0
#> 127.1 3.53 1 62 0 1
#> 124 9.73 1 NA 1 0
#> 10 10.53 1 34 0 0
#> 23 16.92 1 61 0 0
#> 119 24.00 0 17 0 0
#> 27 24.00 0 63 1 0
#> 64 24.00 0 43 0 0
#> 182 24.00 0 35 0 0
#> 182.1 24.00 0 35 0 0
#> 138 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 174 24.00 0 49 1 0
#> 172 24.00 0 41 0 0
#> 143 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 165 24.00 0 47 0 0
#> 131 24.00 0 66 0 0
#> 131.1 24.00 0 66 0 0
#> 137 24.00 0 45 1 0
#> 174.1 24.00 0 49 1 0
#> 75 24.00 0 21 1 0
#> 151 24.00 0 42 0 0
#> 46 24.00 0 71 0 0
#> 80 24.00 0 41 0 0
#> 198 24.00 0 66 0 1
#> 35 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 20 24.00 0 46 1 0
#> 173 24.00 0 19 0 1
#> 126 24.00 0 48 0 0
#> 2 24.00 0 9 0 0
#> 46.1 24.00 0 71 0 0
#> 73 24.00 0 NA 0 1
#> 20.1 24.00 0 46 1 0
#> 75.1 24.00 0 21 1 0
#> 156 24.00 0 50 1 0
#> 116 24.00 0 58 0 1
#> 143.1 24.00 0 51 0 0
#> 116.1 24.00 0 58 0 1
#> 53 24.00 0 32 0 1
#> 53.1 24.00 0 32 0 1
#> 165.1 24.00 0 47 0 0
#> 94 24.00 0 51 0 1
#> 19 24.00 0 57 0 1
#> 72 24.00 0 40 0 1
#> 7 24.00 0 37 1 0
#> 11 24.00 0 42 0 1
#> 84.1 24.00 0 39 0 1
#> 46.2 24.00 0 71 0 0
#> 71 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 75.2 24.00 0 21 1 0
#> 17 24.00 0 38 0 1
#> 182.2 24.00 0 35 0 0
#> 182.3 24.00 0 35 0 0
#> 151.1 24.00 0 42 0 0
#> 178 24.00 0 52 1 0
#> 172.1 24.00 0 41 0 0
#> 118 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 193 24.00 0 45 0 1
#> 138.1 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 11.1 24.00 0 42 0 1
#> 33 24.00 0 53 0 0
#> 19.1 24.00 0 57 0 1
#> 65 24.00 0 57 1 0
#> 144 24.00 0 28 0 1
#> 12 24.00 0 63 0 0
#> 146.1 24.00 0 63 1 0
#> 67 24.00 0 25 0 0
#> 3 24.00 0 31 1 0
#> 173.1 24.00 0 19 0 1
#> 193.1 24.00 0 45 0 1
#> 94.1 24.00 0 51 0 1
#> 160 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 73.1 24.00 0 NA 0 1
#> 185.1 24.00 0 44 1 0
#> 119.1 24.00 0 17 0 0
#> 148.1 24.00 0 61 1 0
#> 35.1 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 62 24.00 0 71 0 0
#> 185.2 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 33.1 24.00 0 53 0 0
#> 196 24.00 0 19 0 0
#> 152.1 24.00 0 36 0 1
#> 7.1 24.00 0 37 1 0
#> 54 24.00 0 53 1 0
#> 132 24.00 0 55 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.22 NA NA NA
#> 2 age, Cure model 0.0271 NA NA NA
#> 3 grade_ii, Cure model -0.230 NA NA NA
#> 4 grade_iii, Cure model 0.542 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00474 NA NA NA
#> 2 grade_ii, Survival model 0.993 NA NA NA
#> 3 grade_iii, Survival model 0.259 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.2209 0.0271 -0.2303 0.5423
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 249.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.2209444 0.0271000 -0.2303001 0.5423489
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00474172 0.99349664 0.25872243
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.758300731 0.373252831 0.588822394 0.231182347 0.984374787 0.007644408
#> [7] 0.588822394 0.460847575 0.802561552 0.784807803 0.470849847 0.333741328
#> [13] 0.057570525 0.186368584 0.304657990 0.262950986 0.231182347 0.373252831
#> [19] 0.115405409 0.628111225 0.441144627 0.740541632 0.510335993 0.608417019
#> [25] 0.128333452 0.952920687 0.219964331 0.151328142 0.903830969 0.968697627
#> [31] 0.304657990 0.057570525 0.895453125 0.151328142 0.373252831 0.520155148
#> [37] 0.441144627 0.569197537 0.870419175 0.091376813 0.976535261 0.676257475
#> [43] 0.713892200 0.057570525 0.758300731 0.647959568 0.920505246 0.784807803
#> [49] 0.186368584 0.749410672 0.026053250 0.569197537 0.174295926 0.470849847
#> [55] 0.628111225 0.647959568 0.936887436 0.139734307 0.549439319 0.695347404
#> [61] 0.007644408 0.402051976 0.402051976 0.811502877 0.853757063 0.520155148
#> [67] 0.026053250 0.284489690 0.273988077 0.608417019 0.231182347 0.695347404
#> [73] 0.363351239 0.829029956 0.304657990 0.333741328 0.820322216 0.676257475
#> [79] 0.758300731 0.294541320 0.713892200 0.091376813 0.920505246 0.421599431
#> [85] 0.186368584 0.490747527 0.853757063 0.870419175 0.829029956 0.500525957
#> [91] 0.952920687 0.936887436 0.829029956 0.421599431 0.333741328 0.903830969
#> [97] 0.713892200 0.647959568 0.026053250 0.539581659 0.984374787 0.887074324
#> [103] 0.559296512 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 180 170 181 99 127 78 181.1 88 81 57 51 150 164
#> 14.82 19.54 16.46 21.19 3.53 23.88 16.46 18.37 14.06 14.46 18.23 20.33 23.60
#> 136 128 90 36 170.1 113 100 179 18 110 85 63 183
#> 21.83 20.35 20.94 21.19 19.54 22.86 16.07 18.63 15.21 17.56 16.44 22.77 9.24
#> 139 169 93 25 128.1 164.1 52 169.1 170.2 111 179.1 130 159
#> 21.49 22.41 10.33 6.32 20.35 23.60 10.42 22.41 19.54 17.45 18.63 16.47 10.55
#> 92 91 6 29 164.2 180.1 125 145 57.1 136.1 157 168 130.1
#> 22.92 5.33 15.64 15.45 23.60 14.82 15.65 10.07 14.46 21.83 15.10 23.72 16.47
#> 66 51.1 100.1 125.1 187 15 45 167 78.1 55 58 60 177
#> 22.13 18.23 16.07 15.65 9.92 22.68 17.42 15.55 23.88 19.34 19.34 13.15 12.53
#> 111.1 168.1 190 32 85.1 99.1 167.1 158 154 128.2 150.1 123 6.1
#> 17.45 23.72 20.81 20.90 16.44 21.19 15.55 20.14 12.63 20.35 20.33 13.00 15.64
#> 180.2 68 29.1 92.1 145.1 76 136.2 40 177.1 159.1 154.1 184 183.1
#> 14.82 20.62 15.45 22.92 10.07 19.22 21.83 18.00 12.53 10.55 12.63 17.77 9.24
#> 187.1 154.2 76.1 150.2 93.1 29.2 125.2 168.2 30 127.1 10 23 119
#> 9.92 12.63 19.22 20.33 10.33 15.45 15.65 23.72 17.43 3.53 10.53 16.92 24.00
#> 27 64 182 182.1 138 148 174 172 143 152 165 131 131.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 174.1 75 151 46 80 198 35 84 20 173 126 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.1 20.1 75.1 156 116 143.1 116.1 53 53.1 165.1 94 19 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 11 84.1 46.2 71 185 75.2 17 182.2 182.3 151.1 178 172.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 146 193 138.1 98 11.1 33 19.1 65 144 12 146.1 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 173.1 193.1 94.1 160 103 185.1 119.1 148.1 35.1 135 62 185.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 33.1 196 152.1 7.1 54 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[29]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.02356989 0.90239987 0.70482006
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.322421160 -0.003736555 0.770925877
#> grade_iii, Cure model
#> 1.271333565
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 61 10.12 1 36 0 1
#> 78 23.88 1 43 0 0
#> 111 17.45 1 47 0 1
#> 108 18.29 1 39 0 1
#> 164 23.60 1 76 0 1
#> 170 19.54 1 43 0 1
#> 81 14.06 1 34 0 0
#> 108.1 18.29 1 39 0 1
#> 180 14.82 1 37 0 0
#> 124 9.73 1 NA 1 0
#> 14 12.89 1 21 0 0
#> 108.2 18.29 1 39 0 1
#> 91 5.33 1 61 0 1
#> 49 12.19 1 48 1 0
#> 25 6.32 1 34 1 0
#> 37 12.52 1 57 1 0
#> 107 11.18 1 54 1 0
#> 16 8.71 1 71 0 1
#> 5 16.43 1 51 0 1
#> 158 20.14 1 74 1 0
#> 61.1 10.12 1 36 0 1
#> 13 14.34 1 54 0 1
#> 101 9.97 1 10 0 1
#> 60 13.15 1 38 1 0
#> 153 21.33 1 55 1 0
#> 97 19.14 1 65 0 1
#> 13.1 14.34 1 54 0 1
#> 55 19.34 1 69 0 1
#> 6 15.64 1 39 0 0
#> 105 19.75 1 60 0 0
#> 123 13.00 1 44 1 0
#> 167 15.55 1 56 1 0
#> 56 12.21 1 60 0 0
#> 199 19.81 1 NA 0 1
#> 4 17.64 1 NA 0 1
#> 90 20.94 1 50 0 1
#> 145 10.07 1 65 1 0
#> 159 10.55 1 50 0 1
#> 14.1 12.89 1 21 0 0
#> 81.1 14.06 1 34 0 0
#> 154 12.63 1 20 1 0
#> 171 16.57 1 41 0 1
#> 136 21.83 1 43 0 1
#> 89 11.44 1 NA 0 0
#> 159.1 10.55 1 50 0 1
#> 89.1 11.44 1 NA 0 0
#> 18 15.21 1 49 1 0
#> 23 16.92 1 61 0 0
#> 101.1 9.97 1 10 0 1
#> 43 12.10 1 61 0 1
#> 179 18.63 1 42 0 0
#> 96 14.54 1 33 0 1
#> 55.1 19.34 1 69 0 1
#> 97.1 19.14 1 65 0 1
#> 128 20.35 1 35 0 1
#> 110 17.56 1 65 0 1
#> 88 18.37 1 47 0 0
#> 159.2 10.55 1 50 0 1
#> 197 21.60 1 69 1 0
#> 134 17.81 1 47 1 0
#> 171.1 16.57 1 41 0 1
#> 158.1 20.14 1 74 1 0
#> 89.2 11.44 1 NA 0 0
#> 166 19.98 1 48 0 0
#> 145.1 10.07 1 65 1 0
#> 107.1 11.18 1 54 1 0
#> 99 21.19 1 38 0 1
#> 183 9.24 1 67 1 0
#> 153.1 21.33 1 55 1 0
#> 113 22.86 1 34 0 0
#> 133 14.65 1 57 0 0
#> 175 21.91 1 43 0 0
#> 16.1 8.71 1 71 0 1
#> 124.1 9.73 1 NA 1 0
#> 93 10.33 1 52 0 1
#> 128.1 20.35 1 35 0 1
#> 70 7.38 1 30 1 0
#> 195 11.76 1 NA 1 0
#> 123.1 13.00 1 44 1 0
#> 113.1 22.86 1 34 0 0
#> 153.2 21.33 1 55 1 0
#> 155 13.08 1 26 0 0
#> 181 16.46 1 45 0 1
#> 134.1 17.81 1 47 1 0
#> 183.1 9.24 1 67 1 0
#> 43.1 12.10 1 61 0 1
#> 106 16.67 1 49 1 0
#> 189 10.51 1 NA 1 0
#> 81.2 14.06 1 34 0 0
#> 155.1 13.08 1 26 0 0
#> 61.2 10.12 1 36 0 1
#> 78.1 23.88 1 43 0 0
#> 197.1 21.60 1 69 1 0
#> 59 10.16 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 123.2 13.00 1 44 1 0
#> 139.1 21.49 1 63 1 0
#> 183.2 9.24 1 67 1 0
#> 128.2 20.35 1 35 0 1
#> 123.3 13.00 1 44 1 0
#> 180.1 14.82 1 37 0 0
#> 45 17.42 1 54 0 1
#> 15 22.68 1 48 0 0
#> 140 12.68 1 59 1 0
#> 49.1 12.19 1 48 1 0
#> 97.2 19.14 1 65 0 1
#> 90.1 20.94 1 50 0 1
#> 129 23.41 1 53 1 0
#> 155.2 13.08 1 26 0 0
#> 154.1 12.63 1 20 1 0
#> 171.2 16.57 1 41 0 1
#> 130 16.47 1 53 0 1
#> 3 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 28 24.00 0 67 1 0
#> 200 24.00 0 64 0 0
#> 95 24.00 0 68 0 1
#> 74 24.00 0 43 0 1
#> 119 24.00 0 17 0 0
#> 102 24.00 0 49 0 0
#> 116 24.00 0 58 0 1
#> 137 24.00 0 45 1 0
#> 200.1 24.00 0 64 0 0
#> 83 24.00 0 6 0 0
#> 21 24.00 0 47 0 0
#> 11 24.00 0 42 0 1
#> 160 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 72 24.00 0 40 0 1
#> 21.1 24.00 0 47 0 0
#> 156 24.00 0 50 1 0
#> 9 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 35 24.00 0 51 0 0
#> 87.1 24.00 0 27 0 0
#> 103 24.00 0 56 1 0
#> 148 24.00 0 61 1 0
#> 19 24.00 0 57 0 1
#> 142 24.00 0 53 0 0
#> 62 24.00 0 71 0 0
#> 118 24.00 0 44 1 0
#> 12 24.00 0 63 0 0
#> 34 24.00 0 36 0 0
#> 122 24.00 0 66 0 0
#> 44 24.00 0 56 0 0
#> 98 24.00 0 34 1 0
#> 3.1 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 120 24.00 0 68 0 1
#> 142.1 24.00 0 53 0 0
#> 62.1 24.00 0 71 0 0
#> 172 24.00 0 41 0 0
#> 132 24.00 0 55 0 0
#> 126 24.00 0 48 0 0
#> 87.2 24.00 0 27 0 0
#> 84 24.00 0 39 0 1
#> 115 24.00 0 NA 1 0
#> 87.3 24.00 0 27 0 0
#> 176 24.00 0 43 0 1
#> 116.1 24.00 0 58 0 1
#> 22 24.00 0 52 1 0
#> 11.1 24.00 0 42 0 1
#> 191 24.00 0 60 0 1
#> 80 24.00 0 41 0 0
#> 152 24.00 0 36 0 1
#> 147.1 24.00 0 76 1 0
#> 22.1 24.00 0 52 1 0
#> 176.1 24.00 0 43 0 1
#> 21.2 24.00 0 47 0 0
#> 126.1 24.00 0 48 0 0
#> 21.3 24.00 0 47 0 0
#> 151 24.00 0 42 0 0
#> 186 24.00 0 45 1 0
#> 35.1 24.00 0 51 0 0
#> 156.1 24.00 0 50 1 0
#> 198.1 24.00 0 66 0 1
#> 156.2 24.00 0 50 1 0
#> 64 24.00 0 43 0 0
#> 109 24.00 0 48 0 0
#> 21.4 24.00 0 47 0 0
#> 67 24.00 0 25 0 0
#> 9.1 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 12.1 24.00 0 63 0 0
#> 185 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 102.1 24.00 0 49 0 0
#> 132.1 24.00 0 55 0 0
#> 146 24.00 0 63 1 0
#> 95.1 24.00 0 68 0 1
#> 27 24.00 0 63 1 0
#> 160.1 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 94 24.00 0 51 0 1
#> 54 24.00 0 53 1 0
#> 156.3 24.00 0 50 1 0
#> 34.1 24.00 0 36 0 0
#> 44.1 24.00 0 56 0 0
#> 1 24.00 0 23 1 0
#> 34.2 24.00 0 36 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.322 NA NA NA
#> 2 age, Cure model -0.00374 NA NA NA
#> 3 grade_ii, Cure model 0.771 NA NA NA
#> 4 grade_iii, Cure model 1.27 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0236 NA NA NA
#> 2 grade_ii, Survival model 0.902 NA NA NA
#> 3 grade_iii, Survival model 0.705 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.322421 -0.003737 0.770926 1.271334
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 247.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.322421160 -0.003736555 0.770925877 1.271333565
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.02356989 0.90239987 0.70482006
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 7.800904e-01 4.029817e-05 2.100636e-01 1.582236e-01 6.336826e-04
#> [6] 9.796989e-02 4.108782e-01 1.582236e-01 3.415988e-01 5.486197e-01
#> [11] 1.582236e-01 9.848360e-01 6.412802e-01 9.697923e-01 6.145530e-01
#> [16] 6.956313e-01 9.247231e-01 2.984778e-01 7.363646e-02 7.800904e-01
#> [21] 3.872918e-01 8.522498e-01 4.474572e-01 2.983168e-02 1.187247e-01
#> [26] 3.872918e-01 1.046815e-01 3.090102e-01 9.137836e-02 4.979823e-01
#> [31] 3.197630e-01 6.278089e-01 4.805549e-02 8.229460e-01 7.234338e-01
#> [36] 5.486197e-01 4.108782e-01 5.885250e-01 2.485421e-01 1.137636e-02
#> [41] 7.234338e-01 3.306406e-01 2.288607e-01 8.522498e-01 6.681687e-01
#> [46] 1.413493e-01 3.756262e-01 1.046815e-01 1.187247e-01 5.838823e-02
#> [51] 2.008872e-01 1.496272e-01 7.234338e-01 1.452947e-02 1.833929e-01
#> [56] 2.485421e-01 7.363646e-02 8.512812e-02 8.229460e-01 6.956313e-01
#> [61] 4.301451e-02 8.809628e-01 2.983168e-02 2.855283e-03 3.639862e-01
#> [66] 8.442800e-03 9.247231e-01 7.656438e-01 5.838823e-02 9.547237e-01
#> [71] 4.979823e-01 2.855283e-03 2.983168e-02 4.599960e-01 2.880890e-01
#> [76] 1.833929e-01 8.809628e-01 6.681687e-01 2.386561e-01 4.108782e-01
#> [81] 4.599960e-01 7.800904e-01 4.029817e-05 1.452947e-02 2.157742e-02
#> [86] 4.979823e-01 2.157742e-02 8.809628e-01 5.838823e-02 4.979823e-01
#> [91] 3.415988e-01 2.193749e-01 6.042958e-03 5.750390e-01 6.412802e-01
#> [96] 1.187247e-01 4.805549e-02 1.622994e-03 4.599960e-01 5.885250e-01
#> [101] 2.485421e-01 2.778112e-01 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 61 78 111 108 164 170 81 108.1 180 14 108.2 91 49
#> 10.12 23.88 17.45 18.29 23.60 19.54 14.06 18.29 14.82 12.89 18.29 5.33 12.19
#> 25 37 107 16 5 158 61.1 13 101 60 153 97 13.1
#> 6.32 12.52 11.18 8.71 16.43 20.14 10.12 14.34 9.97 13.15 21.33 19.14 14.34
#> 55 6 105 123 167 56 90 145 159 14.1 81.1 154 171
#> 19.34 15.64 19.75 13.00 15.55 12.21 20.94 10.07 10.55 12.89 14.06 12.63 16.57
#> 136 159.1 18 23 101.1 43 179 96 55.1 97.1 128 110 88
#> 21.83 10.55 15.21 16.92 9.97 12.10 18.63 14.54 19.34 19.14 20.35 17.56 18.37
#> 159.2 197 134 171.1 158.1 166 145.1 107.1 99 183 153.1 113 133
#> 10.55 21.60 17.81 16.57 20.14 19.98 10.07 11.18 21.19 9.24 21.33 22.86 14.65
#> 175 16.1 93 128.1 70 123.1 113.1 153.2 155 181 134.1 183.1 43.1
#> 21.91 8.71 10.33 20.35 7.38 13.00 22.86 21.33 13.08 16.46 17.81 9.24 12.10
#> 106 81.2 155.1 61.2 78.1 197.1 139 123.2 139.1 183.2 128.2 123.3 180.1
#> 16.67 14.06 13.08 10.12 23.88 21.60 21.49 13.00 21.49 9.24 20.35 13.00 14.82
#> 45 15 140 49.1 97.2 90.1 129 155.2 154.1 171.2 130 3 147
#> 17.42 22.68 12.68 12.19 19.14 20.94 23.41 13.08 12.63 16.57 16.47 24.00 24.00
#> 28 200 95 74 119 102 116 137 200.1 83 21 11 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 72 21.1 156 9 198 35 87.1 103 148 19 142 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 12 34 122 44 98 3.1 173 120 142.1 62.1 172 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 87.2 84 87.3 176 116.1 22 11.1 191 80 152 147.1 22.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 21.2 126.1 21.3 151 186 35.1 156.1 198.1 156.2 64 109 21.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 9.1 12.1 185 20 102.1 132.1 146 95.1 27 160.1 144 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 156.3 34.1 44.1 1 34.2
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[30]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003056462 0.756089509 0.741405778
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.22920852 0.01100014 0.99159476
#> grade_iii, Cure model
#> 1.83815443
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 128 20.35 1 35 0 1
#> 107 11.18 1 54 1 0
#> 111 17.45 1 47 0 1
#> 81 14.06 1 34 0 0
#> 69 23.23 1 25 0 1
#> 170 19.54 1 43 0 1
#> 140 12.68 1 59 1 0
#> 183 9.24 1 67 1 0
#> 129 23.41 1 53 1 0
#> 49 12.19 1 48 1 0
#> 181 16.46 1 45 0 1
#> 183.1 9.24 1 67 1 0
#> 42 12.43 1 49 0 1
#> 192 16.44 1 31 1 0
#> 45 17.42 1 54 0 1
#> 97 19.14 1 65 0 1
#> 150 20.33 1 48 0 0
#> 105 19.75 1 60 0 0
#> 149 8.37 1 33 1 0
#> 194 22.40 1 38 0 1
#> 96 14.54 1 33 0 1
#> 170.1 19.54 1 43 0 1
#> 24 23.89 1 38 0 0
#> 61 10.12 1 36 0 1
#> 40 18.00 1 28 1 0
#> 105.1 19.75 1 60 0 0
#> 57 14.46 1 45 0 1
#> 26 15.77 1 49 0 1
#> 181.1 16.46 1 45 0 1
#> 158 20.14 1 74 1 0
#> 25 6.32 1 34 1 0
#> 117 17.46 1 26 0 1
#> 86 23.81 1 58 0 1
#> 129.1 23.41 1 53 1 0
#> 159 10.55 1 50 0 1
#> 93 10.33 1 52 0 1
#> 158.1 20.14 1 74 1 0
#> 140.1 12.68 1 59 1 0
#> 150.1 20.33 1 48 0 0
#> 41 18.02 1 40 1 0
#> 29 15.45 1 68 1 0
#> 4 17.64 1 NA 0 1
#> 140.2 12.68 1 59 1 0
#> 85 16.44 1 36 0 0
#> 183.2 9.24 1 67 1 0
#> 140.3 12.68 1 59 1 0
#> 175 21.91 1 43 0 0
#> 155 13.08 1 26 0 0
#> 97.1 19.14 1 65 0 1
#> 117.1 17.46 1 26 0 1
#> 188 16.16 1 46 0 1
#> 145 10.07 1 65 1 0
#> 61.1 10.12 1 36 0 1
#> 197 21.60 1 69 1 0
#> 171 16.57 1 41 0 1
#> 107.1 11.18 1 54 1 0
#> 159.1 10.55 1 50 0 1
#> 56 12.21 1 60 0 0
#> 106 16.67 1 49 1 0
#> 106.1 16.67 1 49 1 0
#> 85.1 16.44 1 36 0 0
#> 16 8.71 1 71 0 1
#> 113 22.86 1 34 0 0
#> 199 19.81 1 NA 0 1
#> 61.2 10.12 1 36 0 1
#> 50 10.02 1 NA 1 0
#> 24.1 23.89 1 38 0 0
#> 36 21.19 1 48 0 1
#> 125 15.65 1 67 1 0
#> 154 12.63 1 20 1 0
#> 199.1 19.81 1 NA 0 1
#> 188.1 16.16 1 46 0 1
#> 192.1 16.44 1 31 1 0
#> 108 18.29 1 39 0 1
#> 111.1 17.45 1 47 0 1
#> 10 10.53 1 34 0 0
#> 70 7.38 1 30 1 0
#> 183.3 9.24 1 67 1 0
#> 26.1 15.77 1 49 0 1
#> 93.1 10.33 1 52 0 1
#> 97.2 19.14 1 65 0 1
#> 81.1 14.06 1 34 0 0
#> 16.1 8.71 1 71 0 1
#> 154.1 12.63 1 20 1 0
#> 99 21.19 1 38 0 1
#> 197.1 21.60 1 69 1 0
#> 77 7.27 1 67 0 1
#> 114 13.68 1 NA 0 0
#> 61.3 10.12 1 36 0 1
#> 15 22.68 1 48 0 0
#> 124 9.73 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 24.2 23.89 1 38 0 0
#> 93.2 10.33 1 52 0 1
#> 18 15.21 1 49 1 0
#> 130 16.47 1 53 0 1
#> 110 17.56 1 65 0 1
#> 81.2 14.06 1 34 0 0
#> 117.2 17.46 1 26 0 1
#> 39 15.59 1 37 0 1
#> 169 22.41 1 46 0 0
#> 43 12.10 1 61 0 1
#> 170.2 19.54 1 43 0 1
#> 43.1 12.10 1 61 0 1
#> 188.2 16.16 1 46 0 1
#> 43.2 12.10 1 61 0 1
#> 129.2 23.41 1 53 1 0
#> 40.1 18.00 1 28 1 0
#> 108.1 18.29 1 39 0 1
#> 29.1 15.45 1 68 1 0
#> 123 13.00 1 44 1 0
#> 177 12.53 1 75 0 0
#> 33 24.00 0 53 0 0
#> 165 24.00 0 47 0 0
#> 119 24.00 0 17 0 0
#> 172 24.00 0 41 0 0
#> 122 24.00 0 66 0 0
#> 35 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 64.1 24.00 0 43 0 0
#> 144 24.00 0 28 0 1
#> 122.1 24.00 0 66 0 0
#> 176 24.00 0 43 0 1
#> 196 24.00 0 19 0 0
#> 47 24.00 0 38 0 1
#> 64.2 24.00 0 43 0 0
#> 48 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 173 24.00 0 19 0 1
#> 115 24.00 0 NA 1 0
#> 144.1 24.00 0 28 0 1
#> 137 24.00 0 45 1 0
#> 178 24.00 0 52 1 0
#> 200.1 24.00 0 64 0 0
#> 67 24.00 0 25 0 0
#> 44 24.00 0 56 0 0
#> 112 24.00 0 61 0 0
#> 31 24.00 0 36 0 1
#> 94 24.00 0 51 0 1
#> 151 24.00 0 42 0 0
#> 67.1 24.00 0 25 0 0
#> 48.1 24.00 0 31 1 0
#> 3 24.00 0 31 1 0
#> 119.1 24.00 0 17 0 0
#> 74 24.00 0 43 0 1
#> 44.1 24.00 0 56 0 0
#> 138 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 200.2 24.00 0 64 0 0
#> 67.2 24.00 0 25 0 0
#> 200.3 24.00 0 64 0 0
#> 163 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 163.1 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 34 24.00 0 36 0 0
#> 137.1 24.00 0 45 1 0
#> 172.1 24.00 0 41 0 0
#> 95 24.00 0 68 0 1
#> 162 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 163.2 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 122.2 24.00 0 66 0 0
#> 3.1 24.00 0 31 1 0
#> 196.1 24.00 0 19 0 0
#> 65 24.00 0 57 1 0
#> 48.2 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 73 24.00 0 NA 0 1
#> 137.2 24.00 0 45 1 0
#> 163.3 24.00 0 66 0 0
#> 102 24.00 0 49 0 0
#> 185 24.00 0 44 1 0
#> 141 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 132 24.00 0 55 0 0
#> 174 24.00 0 49 1 0
#> 62 24.00 0 71 0 0
#> 95.1 24.00 0 68 0 1
#> 67.3 24.00 0 25 0 0
#> 38 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 156 24.00 0 50 1 0
#> 176.1 24.00 0 43 0 1
#> 38.1 24.00 0 31 1 0
#> 95.2 24.00 0 68 0 1
#> 7.1 24.00 0 37 1 0
#> 74.1 24.00 0 43 0 1
#> 141.1 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 33.1 24.00 0 53 0 0
#> 126 24.00 0 48 0 0
#> 178.1 24.00 0 52 1 0
#> 196.2 24.00 0 19 0 0
#> 12 24.00 0 63 0 0
#> 138.1 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 72 24.00 0 40 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.23 NA NA NA
#> 2 age, Cure model 0.0110 NA NA NA
#> 3 grade_ii, Cure model 0.992 NA NA NA
#> 4 grade_iii, Cure model 1.84 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00306 NA NA NA
#> 2 grade_ii, Survival model 0.756 NA NA NA
#> 3 grade_iii, Survival model 0.741 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.2292 0.0110 0.9916 1.8382
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 238.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.22920852 0.01100014 0.99159476 1.83815443
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003056462 0.756089509 0.741405778
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.42900395 0.89452488 0.63779748 0.79876725 0.26399848 0.50789230
#> [7] 0.82683171 0.95620890 0.21100404 0.87432524 0.68797593 0.95620890
#> [13] 0.86388144 0.70132033 0.65262584 0.53727671 0.44105433 0.48635564
#> [19] 0.98269110 0.33285347 0.78738447 0.50789230 0.07306374 0.93321112
#> [25] 0.59038136 0.48635564 0.79310462 0.74572634 0.68797593 0.46462548
#> [31] 0.99571305 0.61493273 0.17798118 0.21100404 0.90440286 0.91899969
#> [37] 0.46462548 0.82683171 0.44105433 0.58178237 0.76997408 0.82683171
#> [43] 0.70132033 0.95620890 0.82683171 0.34875344 0.81559609 0.53727671
#> [49] 0.61493273 0.72704848 0.95161098 0.93321112 0.36455239 0.67408371
#> [55] 0.89452488 0.90440286 0.86910650 0.65995899 0.65995899 0.70132033
#> [61] 0.97392246 0.28141288 0.93321112 0.07306374 0.39171444 0.75793642
#> [67] 0.84808451 0.72704848 0.70132033 0.56435173 0.63779748 0.91412731
#> [73] 0.98705876 0.95620890 0.74572634 0.91899969 0.53727671 0.79876725
#> [79] 0.97392246 0.84808451 0.39171444 0.36455239 0.99140079 0.93321112
#> [85] 0.29871044 0.41648381 0.07306374 0.91899969 0.78160887 0.68108181
#> [91] 0.60682632 0.79876725 0.61493273 0.76398726 0.31585147 0.87949869
#> [97] 0.50789230 0.87949869 0.72704848 0.87949869 0.21100404 0.59038136
#> [103] 0.56435173 0.76997408 0.82124150 0.85861055 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 128 107 111 81 69 170 140 183 129 49 181 183.1 42
#> 20.35 11.18 17.45 14.06 23.23 19.54 12.68 9.24 23.41 12.19 16.46 9.24 12.43
#> 192 45 97 150 105 149 194 96 170.1 24 61 40 105.1
#> 16.44 17.42 19.14 20.33 19.75 8.37 22.40 14.54 19.54 23.89 10.12 18.00 19.75
#> 57 26 181.1 158 25 117 86 129.1 159 93 158.1 140.1 150.1
#> 14.46 15.77 16.46 20.14 6.32 17.46 23.81 23.41 10.55 10.33 20.14 12.68 20.33
#> 41 29 140.2 85 183.2 140.3 175 155 97.1 117.1 188 145 61.1
#> 18.02 15.45 12.68 16.44 9.24 12.68 21.91 13.08 19.14 17.46 16.16 10.07 10.12
#> 197 171 107.1 159.1 56 106 106.1 85.1 16 113 61.2 24.1 36
#> 21.60 16.57 11.18 10.55 12.21 16.67 16.67 16.44 8.71 22.86 10.12 23.89 21.19
#> 125 154 188.1 192.1 108 111.1 10 70 183.3 26.1 93.1 97.2 81.1
#> 15.65 12.63 16.16 16.44 18.29 17.45 10.53 7.38 9.24 15.77 10.33 19.14 14.06
#> 16.1 154.1 99 197.1 77 61.3 15 68 24.2 93.2 18 130 110
#> 8.71 12.63 21.19 21.60 7.27 10.12 22.68 20.62 23.89 10.33 15.21 16.47 17.56
#> 81.2 117.2 39 169 43 170.2 43.1 188.2 43.2 129.2 40.1 108.1 29.1
#> 14.06 17.46 15.59 22.41 12.10 19.54 12.10 16.16 12.10 23.41 18.00 18.29 15.45
#> 123 177 33 165 119 172 122 35 64 64.1 144 122.1 176
#> 13.00 12.53 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 47 64.2 48 200 173 144.1 137 178 200.1 67 44 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 94 151 67.1 48.1 3 119.1 74 44.1 138 46 200.2 67.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200.3 163 191 163.1 19 34 137.1 172.1 95 162 83 163.2 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122.2 3.1 196.1 65 48.2 147 137.2 163.3 102 185 141 7 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 62 95.1 67.3 38 118 156 176.1 38.1 95.2 7.1 74.1 141.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 33.1 126 178.1 196.2 12 138.1 160 135 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[31]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01110133 0.58486980 0.09359103
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.161783226 0.004749973 -0.119385728
#> grade_iii, Cure model
#> 0.543391895
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 92 22.92 1 47 0 1
#> 192 16.44 1 31 1 0
#> 69 23.23 1 25 0 1
#> 99 21.19 1 38 0 1
#> 86 23.81 1 58 0 1
#> 149 8.37 1 33 1 0
#> 149.1 8.37 1 33 1 0
#> 79 16.23 1 54 1 0
#> 14 12.89 1 21 0 0
#> 14.1 12.89 1 21 0 0
#> 123 13.00 1 44 1 0
#> 125 15.65 1 67 1 0
#> 8 18.43 1 32 0 0
#> 128 20.35 1 35 0 1
#> 127 3.53 1 62 0 1
#> 36 21.19 1 48 0 1
#> 169 22.41 1 46 0 0
#> 86.1 23.81 1 58 0 1
#> 183 9.24 1 67 1 0
#> 181 16.46 1 45 0 1
#> 26 15.77 1 49 0 1
#> 139 21.49 1 63 1 0
#> 61 10.12 1 36 0 1
#> 90 20.94 1 50 0 1
#> 145 10.07 1 65 1 0
#> 110 17.56 1 65 0 1
#> 154 12.63 1 20 1 0
#> 168 23.72 1 70 0 0
#> 107 11.18 1 54 1 0
#> 177 12.53 1 75 0 0
#> 175 21.91 1 43 0 0
#> 60 13.15 1 38 1 0
#> 158 20.14 1 74 1 0
#> 36.1 21.19 1 48 0 1
#> 129 23.41 1 53 1 0
#> 81 14.06 1 34 0 0
#> 128.1 20.35 1 35 0 1
#> 66 22.13 1 53 0 0
#> 175.1 21.91 1 43 0 0
#> 136 21.83 1 43 0 1
#> 107.1 11.18 1 54 1 0
#> 194 22.40 1 38 0 1
#> 150 20.33 1 48 0 0
#> 66.1 22.13 1 53 0 0
#> 190 20.81 1 42 1 0
#> 88 18.37 1 47 0 0
#> 158.1 20.14 1 74 1 0
#> 42 12.43 1 49 0 1
#> 169.1 22.41 1 46 0 0
#> 139.1 21.49 1 63 1 0
#> 125.1 15.65 1 67 1 0
#> 16 8.71 1 71 0 1
#> 129.1 23.41 1 53 1 0
#> 40 18.00 1 28 1 0
#> 8.1 18.43 1 32 0 0
#> 154.1 12.63 1 20 1 0
#> 69.1 23.23 1 25 0 1
#> 108 18.29 1 39 0 1
#> 68 20.62 1 44 0 0
#> 68.1 20.62 1 44 0 0
#> 113 22.86 1 34 0 0
#> 190.1 20.81 1 42 1 0
#> 168.1 23.72 1 70 0 0
#> 4 17.64 1 NA 0 1
#> 92.1 22.92 1 47 0 1
#> 108.1 18.29 1 39 0 1
#> 114 13.68 1 NA 0 0
#> 123.1 13.00 1 44 1 0
#> 36.2 21.19 1 48 0 1
#> 39 15.59 1 37 0 1
#> 91 5.33 1 61 0 1
#> 159 10.55 1 50 0 1
#> 10 10.53 1 34 0 0
#> 100 16.07 1 60 0 0
#> 59 10.16 1 NA 1 0
#> 189 10.51 1 NA 1 0
#> 56 12.21 1 60 0 0
#> 188 16.16 1 46 0 1
#> 23 16.92 1 61 0 0
#> 45 17.42 1 54 0 1
#> 10.1 10.53 1 34 0 0
#> 86.2 23.81 1 58 0 1
#> 93 10.33 1 52 0 1
#> 111 17.45 1 47 0 1
#> 166 19.98 1 48 0 0
#> 129.2 23.41 1 53 1 0
#> 8.2 18.43 1 32 0 0
#> 188.1 16.16 1 46 0 1
#> 30 17.43 1 78 0 0
#> 154.2 12.63 1 20 1 0
#> 25 6.32 1 34 1 0
#> 89 11.44 1 NA 0 0
#> 37 12.52 1 57 1 0
#> 76 19.22 1 54 0 1
#> 93.1 10.33 1 52 0 1
#> 61.1 10.12 1 36 0 1
#> 171 16.57 1 41 0 1
#> 45.1 17.42 1 54 0 1
#> 169.2 22.41 1 46 0 0
#> 189.1 10.51 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 93.2 10.33 1 52 0 1
#> 56.1 12.21 1 60 0 0
#> 70 7.38 1 30 1 0
#> 42.1 12.43 1 49 0 1
#> 194.1 22.40 1 38 0 1
#> 89.1 11.44 1 NA 0 0
#> 155 13.08 1 26 0 0
#> 45.2 17.42 1 54 0 1
#> 123.2 13.00 1 44 1 0
#> 166.1 19.98 1 48 0 0
#> 125.2 15.65 1 67 1 0
#> 131 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 34 24.00 0 36 0 0
#> 3 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 64 24.00 0 43 0 0
#> 47 24.00 0 38 0 1
#> 84 24.00 0 39 0 1
#> 28 24.00 0 67 1 0
#> 142 24.00 0 53 0 0
#> 146 24.00 0 63 1 0
#> 178 24.00 0 52 1 0
#> 35 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 67 24.00 0 25 0 0
#> 161 24.00 0 45 0 0
#> 131.1 24.00 0 66 0 0
#> 120.1 24.00 0 68 0 1
#> 20 24.00 0 46 1 0
#> 156 24.00 0 50 1 0
#> 160 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 138 24.00 0 44 1 0
#> 94 24.00 0 51 0 1
#> 131.2 24.00 0 66 0 0
#> 115 24.00 0 NA 1 0
#> 137 24.00 0 45 1 0
#> 120.2 24.00 0 68 0 1
#> 137.1 24.00 0 45 1 0
#> 38 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 75 24.00 0 21 1 0
#> 191 24.00 0 60 0 1
#> 116 24.00 0 58 0 1
#> 132 24.00 0 55 0 0
#> 172 24.00 0 41 0 0
#> 35.1 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 156.1 24.00 0 50 1 0
#> 12 24.00 0 63 0 0
#> 44 24.00 0 56 0 0
#> 3.1 24.00 0 31 1 0
#> 38.1 24.00 0 31 1 0
#> 64.1 24.00 0 43 0 0
#> 64.2 24.00 0 43 0 0
#> 198 24.00 0 66 0 1
#> 160.1 24.00 0 31 1 0
#> 84.1 24.00 0 39 0 1
#> 173 24.00 0 19 0 1
#> 27 24.00 0 63 1 0
#> 72 24.00 0 40 0 1
#> 44.1 24.00 0 56 0 0
#> 95 24.00 0 68 0 1
#> 75.1 24.00 0 21 1 0
#> 151 24.00 0 42 0 0
#> 87 24.00 0 27 0 0
#> 53 24.00 0 32 0 1
#> 17 24.00 0 38 0 1
#> 185 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 173.1 24.00 0 19 0 1
#> 160.2 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 83 24.00 0 6 0 0
#> 200 24.00 0 64 0 0
#> 118 24.00 0 44 1 0
#> 160.3 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 35.2 24.00 0 51 0 0
#> 47.1 24.00 0 38 0 1
#> 135.1 24.00 0 58 1 0
#> 173.2 24.00 0 19 0 1
#> 138.1 24.00 0 44 1 0
#> 94.1 24.00 0 51 0 1
#> 200.1 24.00 0 64 0 0
#> 104 24.00 0 50 1 0
#> 11 24.00 0 42 0 1
#> 115.1 24.00 0 NA 1 0
#> 160.4 24.00 0 31 1 0
#> 17.1 24.00 0 38 0 1
#> 151.1 24.00 0 42 0 0
#> 178.1 24.00 0 52 1 0
#> 98 24.00 0 34 1 0
#> 163.1 24.00 0 66 0 0
#> 135.2 24.00 0 58 1 0
#> 94.2 24.00 0 51 0 1
#> 172.1 24.00 0 41 0 0
#> 146.1 24.00 0 63 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.162 NA NA NA
#> 2 age, Cure model 0.00475 NA NA NA
#> 3 grade_ii, Cure model -0.119 NA NA NA
#> 4 grade_iii, Cure model 0.543 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0111 NA NA NA
#> 2 grade_ii, Survival model 0.585 NA NA NA
#> 3 grade_iii, Survival model 0.0936 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.16178 0.00475 -0.11939 0.54339
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 258.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.161783226 0.004749973 -0.119385728 0.543391895
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01110133 0.58486980 0.09359103
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0462803918 0.4607605018 0.0359969871 0.1483319902 0.0034716225
#> [6] 0.9261165141 0.9261165141 0.4718110403 0.6425244187 0.6425244187
#> [11] 0.6083263720 0.5278477358 0.2959625677 0.2226845556 0.9875889589
#> [16] 0.1483319902 0.0635078022 0.0034716225 0.9013246845 0.4496373718
#> [21] 0.5164101220 0.1327373923 0.8645517562 0.1800214582 0.8889957070
#> [26] 0.3649790668 0.6657029465 0.0122051575 0.7691180693 0.6994037262
#> [31] 0.1097304076 0.5850084986 0.2494299150 0.1483319902 0.0223512070
#> [36] 0.5733370490 0.2226845556 0.0954076945 0.1097304076 0.1248016564
#> [41] 0.7691180693 0.0819832938 0.2403090610 0.0954076945 0.1886792675
#> [46] 0.3247660411 0.2494299150 0.7224631748 0.0635078022 0.1327373923
#> [51] 0.5278477358 0.9136784940 0.0223512070 0.3548794806 0.2959625677
#> [56] 0.6657029465 0.0359969871 0.3347901459 0.2054098083 0.2054098083
#> [61] 0.0574342985 0.1886792675 0.0122051575 0.0462803918 0.3347901459
#> [66] 0.6083263720 0.1483319902 0.5617398277 0.9752474434 0.7926334456
#> [71] 0.8045454671 0.5050636406 0.7456131659 0.4828653437 0.4276568191
#> [76] 0.3960330699 0.8045454671 0.0034716225 0.8284137367 0.3752106959
#> [81] 0.2676136481 0.0223512070 0.2959625677 0.4828653437 0.3855404465
#> [86] 0.6657029465 0.9629745928 0.7109290752 0.2863228001 0.8284137367
#> [91] 0.8645517562 0.4386053129 0.3960330699 0.0635078022 0.0007556637
#> [96] 0.8284137367 0.7456131659 0.9506655843 0.7224631748 0.0819832938
#> [101] 0.5966388730 0.3960330699 0.6083263720 0.2676136481 0.5278477358
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000
#>
#> $Time
#> 92 192 69 99 86 149 149.1 79 14 14.1 123 125 8
#> 22.92 16.44 23.23 21.19 23.81 8.37 8.37 16.23 12.89 12.89 13.00 15.65 18.43
#> 128 127 36 169 86.1 183 181 26 139 61 90 145 110
#> 20.35 3.53 21.19 22.41 23.81 9.24 16.46 15.77 21.49 10.12 20.94 10.07 17.56
#> 154 168 107 177 175 60 158 36.1 129 81 128.1 66 175.1
#> 12.63 23.72 11.18 12.53 21.91 13.15 20.14 21.19 23.41 14.06 20.35 22.13 21.91
#> 136 107.1 194 150 66.1 190 88 158.1 42 169.1 139.1 125.1 16
#> 21.83 11.18 22.40 20.33 22.13 20.81 18.37 20.14 12.43 22.41 21.49 15.65 8.71
#> 129.1 40 8.1 154.1 69.1 108 68 68.1 113 190.1 168.1 92.1 108.1
#> 23.41 18.00 18.43 12.63 23.23 18.29 20.62 20.62 22.86 20.81 23.72 22.92 18.29
#> 123.1 36.2 39 91 159 10 100 56 188 23 45 10.1 86.2
#> 13.00 21.19 15.59 5.33 10.55 10.53 16.07 12.21 16.16 16.92 17.42 10.53 23.81
#> 93 111 166 129.2 8.2 188.1 30 154.2 25 37 76 93.1 61.1
#> 10.33 17.45 19.98 23.41 18.43 16.16 17.43 12.63 6.32 12.52 19.22 10.33 10.12
#> 171 45.1 169.2 24 93.2 56.1 70 42.1 194.1 155 45.2 123.2 166.1
#> 16.57 17.42 22.41 23.89 10.33 12.21 7.38 12.43 22.40 13.08 17.42 13.00 19.98
#> 125.2 131 120 34 3 186 64 47 84 28 142 146 178
#> 15.65 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 163 67 161 131.1 120.1 20 156 160 109 138 94 131.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 120.2 137.1 38 143 75 191 116 132 172 35.1 135 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 44 3.1 38.1 64.1 64.2 198 160.1 84.1 173 27 72 44.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 75.1 151 87 53 17 185 31 173.1 160.2 21 83 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 160.3 148 35.2 47.1 135.1 173.2 138.1 94.1 200.1 104 11 160.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.1 151.1 178.1 98 163.1 135.2 94.2 172.1 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[32]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004535393 0.395634662 0.189763923
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.383477644 0.009068203 -0.151010742
#> grade_iii, Cure model
#> 0.590409392
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 51 18.23 1 83 0 1
#> 170 19.54 1 43 0 1
#> 15 22.68 1 48 0 0
#> 105 19.75 1 60 0 0
#> 149 8.37 1 33 1 0
#> 195 11.76 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 153 21.33 1 55 1 0
#> 5 16.43 1 51 0 1
#> 157 15.10 1 47 0 0
#> 105.1 19.75 1 60 0 0
#> 42 12.43 1 49 0 1
#> 69 23.23 1 25 0 1
#> 129 23.41 1 53 1 0
#> 129.1 23.41 1 53 1 0
#> 108 18.29 1 39 0 1
#> 86 23.81 1 58 0 1
#> 96 14.54 1 33 0 1
#> 52 10.42 1 52 0 1
#> 169 22.41 1 46 0 0
#> 81 14.06 1 34 0 0
#> 49 12.19 1 48 1 0
#> 40 18.00 1 28 1 0
#> 86.1 23.81 1 58 0 1
#> 190 20.81 1 42 1 0
#> 91 5.33 1 61 0 1
#> 24 23.89 1 38 0 0
#> 85 16.44 1 36 0 0
#> 92 22.92 1 47 0 1
#> 77 7.27 1 67 0 1
#> 154 12.63 1 20 1 0
#> 168 23.72 1 70 0 0
#> 184 17.77 1 38 0 0
#> 8 18.43 1 32 0 0
#> 117 17.46 1 26 0 1
#> 68 20.62 1 44 0 0
#> 184.1 17.77 1 38 0 0
#> 136 21.83 1 43 0 1
#> 57 14.46 1 45 0 1
#> 124 9.73 1 NA 1 0
#> 153.1 21.33 1 55 1 0
#> 168.1 23.72 1 70 0 0
#> 155 13.08 1 26 0 0
#> 133 14.65 1 57 0 0
#> 78 23.88 1 43 0 0
#> 153.2 21.33 1 55 1 0
#> 6 15.64 1 39 0 0
#> 133.1 14.65 1 57 0 0
#> 49.1 12.19 1 48 1 0
#> 171 16.57 1 41 0 1
#> 57.1 14.46 1 45 0 1
#> 127 3.53 1 62 0 1
#> 86.2 23.81 1 58 0 1
#> 66 22.13 1 53 0 0
#> 36 21.19 1 48 0 1
#> 52.1 10.42 1 52 0 1
#> 123 13.00 1 44 1 0
#> 68.1 20.62 1 44 0 0
#> 149.1 8.37 1 33 1 0
#> 145 10.07 1 65 1 0
#> 181 16.46 1 45 0 1
#> 130 16.47 1 53 0 1
#> 66.1 22.13 1 53 0 0
#> 89 11.44 1 NA 0 0
#> 45 17.42 1 54 0 1
#> 99 21.19 1 38 0 1
#> 92.1 22.92 1 47 0 1
#> 60 13.15 1 38 1 0
#> 68.2 20.62 1 44 0 0
#> 96.1 14.54 1 33 0 1
#> 133.2 14.65 1 57 0 0
#> 190.1 20.81 1 42 1 0
#> 91.1 5.33 1 61 0 1
#> 41 18.02 1 40 1 0
#> 52.2 10.42 1 52 0 1
#> 85.1 16.44 1 36 0 0
#> 18 15.21 1 49 1 0
#> 157.1 15.10 1 47 0 0
#> 105.2 19.75 1 60 0 0
#> 16 8.71 1 71 0 1
#> 113 22.86 1 34 0 0
#> 97 19.14 1 65 0 1
#> 37 12.52 1 57 1 0
#> 50 10.02 1 NA 1 0
#> 86.3 23.81 1 58 0 1
#> 6.1 15.64 1 39 0 0
#> 77.1 7.27 1 67 0 1
#> 85.2 16.44 1 36 0 0
#> 30 17.43 1 78 0 0
#> 29 15.45 1 68 1 0
#> 164 23.60 1 76 0 1
#> 128 20.35 1 35 0 1
#> 5.1 16.43 1 51 0 1
#> 169.1 22.41 1 46 0 0
#> 10 10.53 1 34 0 0
#> 26 15.77 1 49 0 1
#> 99.1 21.19 1 38 0 1
#> 25 6.32 1 34 1 0
#> 26.1 15.77 1 49 0 1
#> 188 16.16 1 46 0 1
#> 111 17.45 1 47 0 1
#> 90 20.94 1 50 0 1
#> 60.1 13.15 1 38 1 0
#> 29.1 15.45 1 68 1 0
#> 63 22.77 1 31 1 0
#> 130.1 16.47 1 53 0 1
#> 63.1 22.77 1 31 1 0
#> 18.1 15.21 1 49 1 0
#> 177 12.53 1 75 0 0
#> 108.1 18.29 1 39 0 1
#> 111.1 17.45 1 47 0 1
#> 114 13.68 1 NA 0 0
#> 193 24.00 0 45 0 1
#> 142 24.00 0 53 0 0
#> 119 24.00 0 17 0 0
#> 53 24.00 0 32 0 1
#> 72 24.00 0 40 0 1
#> 172 24.00 0 41 0 0
#> 119.1 24.00 0 17 0 0
#> 109 24.00 0 48 0 0
#> 118 24.00 0 44 1 0
#> 193.1 24.00 0 45 0 1
#> 163 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 142.1 24.00 0 53 0 0
#> 152 24.00 0 36 0 1
#> 7 24.00 0 37 1 0
#> 126 24.00 0 48 0 0
#> 28 24.00 0 67 1 0
#> 53.1 24.00 0 32 0 1
#> 142.2 24.00 0 53 0 0
#> 46 24.00 0 71 0 0
#> 156 24.00 0 50 1 0
#> 118.1 24.00 0 44 1 0
#> 126.1 24.00 0 48 0 0
#> 38 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 9.1 24.00 0 31 1 0
#> 172.1 24.00 0 41 0 0
#> 12 24.00 0 63 0 0
#> 131 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 17 24.00 0 38 0 1
#> 186 24.00 0 45 1 0
#> 148 24.00 0 61 1 0
#> 174 24.00 0 49 1 0
#> 200 24.00 0 64 0 0
#> 98 24.00 0 34 1 0
#> 196 24.00 0 19 0 0
#> 178 24.00 0 52 1 0
#> 156.1 24.00 0 50 1 0
#> 95 24.00 0 68 0 1
#> 28.1 24.00 0 67 1 0
#> 3 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 31 24.00 0 36 0 1
#> 178.1 24.00 0 52 1 0
#> 120.1 24.00 0 68 0 1
#> 53.2 24.00 0 32 0 1
#> 161 24.00 0 45 0 0
#> 75 24.00 0 21 1 0
#> 147.1 24.00 0 76 1 0
#> 67 24.00 0 25 0 0
#> 135 24.00 0 58 1 0
#> 72.1 24.00 0 40 0 1
#> 200.1 24.00 0 64 0 0
#> 11 24.00 0 42 0 1
#> 135.1 24.00 0 58 1 0
#> 71 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 146 24.00 0 63 1 0
#> 103 24.00 0 56 1 0
#> 34 24.00 0 36 0 0
#> 172.2 24.00 0 41 0 0
#> 2 24.00 0 9 0 0
#> 191 24.00 0 60 0 1
#> 35 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 94 24.00 0 51 0 1
#> 120.2 24.00 0 68 0 1
#> 17.1 24.00 0 38 0 1
#> 121 24.00 0 57 1 0
#> 34.1 24.00 0 36 0 0
#> 82 24.00 0 34 0 0
#> 72.2 24.00 0 40 0 1
#> 165 24.00 0 47 0 0
#> 75.1 24.00 0 21 1 0
#> 46.1 24.00 0 71 0 0
#> 182 24.00 0 35 0 0
#> 120.3 24.00 0 68 0 1
#> 83 24.00 0 6 0 0
#> 2.1 24.00 0 9 0 0
#> 116 24.00 0 58 0 1
#> 151 24.00 0 42 0 0
#> 104 24.00 0 50 1 0
#> 74 24.00 0 43 0 1
#> 176 24.00 0 43 0 1
#> 21 24.00 0 47 0 0
#> 141.1 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.383 NA NA NA
#> 2 age, Cure model 0.00907 NA NA NA
#> 3 grade_ii, Cure model -0.151 NA NA NA
#> 4 grade_iii, Cure model 0.590 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00454 NA NA NA
#> 2 grade_ii, Survival model 0.396 NA NA NA
#> 3 grade_iii, Survival model 0.190 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.383478 0.009068 -0.151011 0.590409
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 261 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.383477644 0.009068203 -0.151010742 0.590409392
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004535393 0.395634662 0.189763923
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.409369909 0.352996393 0.153747161 0.325625106 0.923868093 0.381191922
#> [7] 0.209101861 0.569639218 0.674581574 0.325625106 0.837949995 0.099400580
#> [13] 0.081431333 0.081431333 0.390664969 0.025382521 0.722404679 0.876191227
#> [19] 0.162892999 0.760924210 0.847565573 0.428317156 0.025382521 0.271716251
#> [25] 0.971427523 0.004242676 0.541370219 0.108762915 0.942858397 0.809113543
#> [31] 0.053372826 0.437701407 0.371763865 0.456394347 0.289588703 0.437701407
#> [37] 0.199597444 0.741660873 0.209101861 0.053372826 0.789814967 0.693682673
#> [43] 0.013919375 0.209101861 0.617326290 0.693682673 0.847565573 0.503499349
#> [49] 0.741660873 0.990439762 0.025382521 0.181045871 0.235796980 0.876191227
#> [55] 0.799476868 0.289588703 0.923868093 0.904681049 0.531854580 0.512998316
#> [61] 0.181045871 0.493999702 0.235796980 0.108762915 0.770635300 0.289588703
#> [67] 0.722404679 0.693682673 0.271716251 0.971427523 0.418869120 0.876191227
#> [73] 0.541370219 0.655583774 0.674581574 0.325625106 0.914268336 0.126756878
#> [79] 0.362368008 0.828337943 0.025382521 0.617326290 0.942858397 0.541370219
#> [85] 0.484509852 0.636481208 0.071506864 0.316423203 0.569639218 0.162892999
#> [91] 0.866604010 0.598267286 0.235796980 0.961890049 0.598267286 0.588670528
#> [97] 0.465824004 0.262487699 0.770635300 0.636481208 0.136197747 0.512998316
#> [103] 0.136197747 0.655583774 0.818709473 0.390664969 0.465824004 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000
#>
#> $Time
#> 51 170 15 105 149 88 153 5 157 105.1 42 69 129
#> 18.23 19.54 22.68 19.75 8.37 18.37 21.33 16.43 15.10 19.75 12.43 23.23 23.41
#> 129.1 108 86 96 52 169 81 49 40 86.1 190 91 24
#> 23.41 18.29 23.81 14.54 10.42 22.41 14.06 12.19 18.00 23.81 20.81 5.33 23.89
#> 85 92 77 154 168 184 8 117 68 184.1 136 57 153.1
#> 16.44 22.92 7.27 12.63 23.72 17.77 18.43 17.46 20.62 17.77 21.83 14.46 21.33
#> 168.1 155 133 78 153.2 6 133.1 49.1 171 57.1 127 86.2 66
#> 23.72 13.08 14.65 23.88 21.33 15.64 14.65 12.19 16.57 14.46 3.53 23.81 22.13
#> 36 52.1 123 68.1 149.1 145 181 130 66.1 45 99 92.1 60
#> 21.19 10.42 13.00 20.62 8.37 10.07 16.46 16.47 22.13 17.42 21.19 22.92 13.15
#> 68.2 96.1 133.2 190.1 91.1 41 52.2 85.1 18 157.1 105.2 16 113
#> 20.62 14.54 14.65 20.81 5.33 18.02 10.42 16.44 15.21 15.10 19.75 8.71 22.86
#> 97 37 86.3 6.1 77.1 85.2 30 29 164 128 5.1 169.1 10
#> 19.14 12.52 23.81 15.64 7.27 16.44 17.43 15.45 23.60 20.35 16.43 22.41 10.53
#> 26 99.1 25 26.1 188 111 90 60.1 29.1 63 130.1 63.1 18.1
#> 15.77 21.19 6.32 15.77 16.16 17.45 20.94 13.15 15.45 22.77 16.47 22.77 15.21
#> 177 108.1 111.1 193 142 119 53 72 172 119.1 109 118 193.1
#> 12.53 18.29 17.45 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 147 142.1 152 7 126 28 53.1 142.2 46 156 118.1 126.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 141 9 9.1 172.1 12 131 84 17 186 148 174 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 196 178 156.1 95 28.1 3 120 31 178.1 120.1 53.2 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 147.1 67 135 72.1 200.1 11 135.1 71 44 146 103 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.2 2 191 35 94 120.2 17.1 121 34.1 82 72.2 165 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.1 182 120.3 83 2.1 116 151 104 74 176 21 141.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[33]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0195820 0.4579794 0.3229982
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.305332003 0.003965913 0.052861600
#> grade_iii, Cure model
#> 1.110022900
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 107 11.18 1 54 1 0
#> 164 23.60 1 76 0 1
#> 66 22.13 1 53 0 0
#> 133 14.65 1 57 0 0
#> 136 21.83 1 43 0 1
#> 14 12.89 1 21 0 0
#> 70 7.38 1 30 1 0
#> 42 12.43 1 49 0 1
#> 70.1 7.38 1 30 1 0
#> 184 17.77 1 38 0 0
#> 24 23.89 1 38 0 0
#> 168 23.72 1 70 0 0
#> 56 12.21 1 60 0 0
#> 43 12.10 1 61 0 1
#> 106 16.67 1 49 1 0
#> 168.1 23.72 1 70 0 0
#> 189 10.51 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 128 20.35 1 35 0 1
#> 50 10.02 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 171 16.57 1 41 0 1
#> 111 17.45 1 47 0 1
#> 60 13.15 1 38 1 0
#> 8 18.43 1 32 0 0
#> 63 22.77 1 31 1 0
#> 29 15.45 1 68 1 0
#> 129 23.41 1 53 1 0
#> 6 15.64 1 39 0 0
#> 45 17.42 1 54 0 1
#> 127 3.53 1 62 0 1
#> 108 18.29 1 39 0 1
#> 106.1 16.67 1 49 1 0
#> 136.1 21.83 1 43 0 1
#> 59 10.16 1 NA 1 0
#> 133.1 14.65 1 57 0 0
#> 88 18.37 1 47 0 0
#> 134 17.81 1 47 1 0
#> 18 15.21 1 49 1 0
#> 155 13.08 1 26 0 0
#> 190 20.81 1 42 1 0
#> 177 12.53 1 75 0 0
#> 16 8.71 1 71 0 1
#> 128.1 20.35 1 35 0 1
#> 43.1 12.10 1 61 0 1
#> 105 19.75 1 60 0 0
#> 14.1 12.89 1 21 0 0
#> 14.2 12.89 1 21 0 0
#> 139 21.49 1 63 1 0
#> 93 10.33 1 52 0 1
#> 6.1 15.64 1 39 0 0
#> 85 16.44 1 36 0 0
#> 192.1 16.44 1 31 1 0
#> 6.2 15.64 1 39 0 0
#> 26 15.77 1 49 0 1
#> 15 22.68 1 48 0 0
#> 195 11.76 1 NA 1 0
#> 60.1 13.15 1 38 1 0
#> 57 14.46 1 45 0 1
#> 194 22.40 1 38 0 1
#> 195.1 11.76 1 NA 1 0
#> 10 10.53 1 34 0 0
#> 42.1 12.43 1 49 0 1
#> 167 15.55 1 56 1 0
#> 133.2 14.65 1 57 0 0
#> 192.2 16.44 1 31 1 0
#> 128.2 20.35 1 35 0 1
#> 40 18.00 1 28 1 0
#> 43.2 12.10 1 61 0 1
#> 123 13.00 1 44 1 0
#> 158 20.14 1 74 1 0
#> 81 14.06 1 34 0 0
#> 117 17.46 1 26 0 1
#> 184.1 17.77 1 38 0 0
#> 29.1 15.45 1 68 1 0
#> 170 19.54 1 43 0 1
#> 169 22.41 1 46 0 0
#> 101 9.97 1 10 0 1
#> 169.1 22.41 1 46 0 0
#> 14.3 12.89 1 21 0 0
#> 175 21.91 1 43 0 0
#> 127.1 3.53 1 62 0 1
#> 39 15.59 1 37 0 1
#> 86 23.81 1 58 0 1
#> 42.2 12.43 1 49 0 1
#> 164.1 23.60 1 76 0 1
#> 16.1 8.71 1 71 0 1
#> 86.1 23.81 1 58 0 1
#> 168.2 23.72 1 70 0 0
#> 100 16.07 1 60 0 0
#> 50.1 10.02 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 25 6.32 1 34 1 0
#> 106.2 16.67 1 49 1 0
#> 153 21.33 1 55 1 0
#> 175.1 21.91 1 43 0 0
#> 93.1 10.33 1 52 0 1
#> 8.1 18.43 1 32 0 0
#> 70.2 7.38 1 30 1 0
#> 61 10.12 1 36 0 1
#> 108.1 18.29 1 39 0 1
#> 124 9.73 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 51 18.23 1 83 0 1
#> 41 18.02 1 40 1 0
#> 197 21.60 1 69 1 0
#> 4 17.64 1 NA 0 1
#> 168.3 23.72 1 70 0 0
#> 181 16.46 1 45 0 1
#> 106.3 16.67 1 49 1 0
#> 52 10.42 1 52 0 1
#> 68 20.62 1 44 0 0
#> 137 24.00 0 45 1 0
#> 33 24.00 0 53 0 0
#> 119 24.00 0 17 0 0
#> 11 24.00 0 42 0 1
#> 143 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 193 24.00 0 45 0 1
#> 64 24.00 0 43 0 0
#> 2 24.00 0 9 0 0
#> 104 24.00 0 50 1 0
#> 35 24.00 0 51 0 0
#> 2.1 24.00 0 9 0 0
#> 22 24.00 0 52 1 0
#> 19 24.00 0 57 0 1
#> 162 24.00 0 51 0 0
#> 137.1 24.00 0 45 1 0
#> 20 24.00 0 46 1 0
#> 80 24.00 0 41 0 0
#> 161 24.00 0 45 0 0
#> 165 24.00 0 47 0 0
#> 160 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 94 24.00 0 51 0 1
#> 17 24.00 0 38 0 1
#> 12 24.00 0 63 0 0
#> 35.1 24.00 0 51 0 0
#> 174 24.00 0 49 1 0
#> 17.1 24.00 0 38 0 1
#> 34 24.00 0 36 0 0
#> 135 24.00 0 58 1 0
#> 21 24.00 0 47 0 0
#> 146 24.00 0 63 1 0
#> 126 24.00 0 48 0 0
#> 147 24.00 0 76 1 0
#> 151 24.00 0 42 0 0
#> 121 24.00 0 57 1 0
#> 62 24.00 0 71 0 0
#> 31 24.00 0 36 0 1
#> 65 24.00 0 57 1 0
#> 160.1 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 174.1 24.00 0 49 1 0
#> 132 24.00 0 55 0 0
#> 46 24.00 0 71 0 0
#> 94.1 24.00 0 51 0 1
#> 74 24.00 0 43 0 1
#> 28 24.00 0 67 1 0
#> 122 24.00 0 66 0 0
#> 132.1 24.00 0 55 0 0
#> 11.1 24.00 0 42 0 1
#> 21.1 24.00 0 47 0 0
#> 143.1 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 87 24.00 0 27 0 0
#> 196 24.00 0 19 0 0
#> 142 24.00 0 53 0 0
#> 165.1 24.00 0 47 0 0
#> 146.1 24.00 0 63 1 0
#> 182 24.00 0 35 0 0
#> 12.1 24.00 0 63 0 0
#> 143.2 24.00 0 51 0 0
#> 80.1 24.00 0 41 0 0
#> 156 24.00 0 50 1 0
#> 193.1 24.00 0 45 0 1
#> 118.1 24.00 0 44 1 0
#> 138.1 24.00 0 44 1 0
#> 19.1 24.00 0 57 0 1
#> 73 24.00 0 NA 0 1
#> 98 24.00 0 34 1 0
#> 160.2 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 75 24.00 0 21 1 0
#> 103 24.00 0 56 1 0
#> 95 24.00 0 68 0 1
#> 142.1 24.00 0 53 0 0
#> 34.1 24.00 0 36 0 0
#> 182.1 24.00 0 35 0 0
#> 172 24.00 0 41 0 0
#> 7 24.00 0 37 1 0
#> 151.1 24.00 0 42 0 0
#> 54 24.00 0 53 1 0
#> 82 24.00 0 34 0 0
#> 196.1 24.00 0 19 0 0
#> 72 24.00 0 40 0 1
#> 103.1 24.00 0 56 1 0
#> 178.1 24.00 0 52 1 0
#> 161.1 24.00 0 45 0 0
#> 34.2 24.00 0 36 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.305 NA NA NA
#> 2 age, Cure model 0.00397 NA NA NA
#> 3 grade_ii, Cure model 0.0529 NA NA NA
#> 4 grade_iii, Cure model 1.11 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0196 NA NA NA
#> 2 grade_ii, Survival model 0.458 NA NA NA
#> 3 grade_iii, Survival model 0.323 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.305332 0.003966 0.052862 1.110023
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 252.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.305332003 0.003965913 0.052861600 1.110022900
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0195820 0.4579794 0.3229982
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 7.460713e-01 2.948856e-03 1.962651e-02 4.489047e-01 2.979280e-02
#> [6] 5.692614e-01 8.960459e-01 6.395328e-01 8.960459e-01 1.785538e-01
#> [11] 1.540355e-05 5.484821e-04 6.838991e-01 6.992543e-01 2.325800e-01
#> [16] 5.484821e-04 2.915052e-01 6.155022e-02 2.230310e-01 2.708235e-01
#> [21] 2.046913e-01 5.143720e-01 1.089223e-01 7.602255e-03 4.120430e-01
#> [26] 5.741299e-03 3.543503e-01 2.137588e-01 9.646842e-01 1.304311e-01
#> [31] 2.325800e-01 2.979280e-02 4.489047e-01 1.229436e-01 1.701488e-01
#> [36] 4.364078e-01 5.414453e-01 5.131667e-02 6.248789e-01 8.618221e-01
#> [41] 6.155022e-02 6.992543e-01 8.907823e-02 5.692614e-01 5.692614e-01
#> [46] 4.186118e-02 7.948747e-01 3.543503e-01 2.915052e-01 2.915052e-01
#> [51] 3.543503e-01 3.432372e-01 9.530730e-03 5.143720e-01 4.874682e-01
#> [56] 1.673857e-02 7.621703e-01 6.395328e-01 4.000931e-01 4.489047e-01
#> [61] 2.915052e-01 6.155022e-02 1.618947e-01 6.992543e-01 5.552955e-01
#> [66] 8.296438e-02 5.008323e-01 1.958009e-01 1.785538e-01 4.120430e-01
#> [71] 9.549659e-02 1.173119e-02 8.449802e-01 1.173119e-02 5.692614e-01
#> [76] 2.281806e-02 9.646842e-01 3.883093e-01 1.263655e-04 6.395328e-01
#> [81] 2.948856e-03 8.618221e-01 1.263655e-04 5.484821e-04 3.322910e-01
#> [86] 1.020946e-01 9.472418e-01 2.325800e-01 4.647789e-02 2.281806e-02
#> [91] 7.948747e-01 1.089223e-01 8.960459e-01 8.280926e-01 1.304311e-01
#> [96] 7.712137e-02 1.455795e-01 1.536770e-01 3.750398e-02 5.484821e-04
#> [101] 2.810830e-01 2.325800e-01 7.784365e-01 5.629918e-02 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00
#>
#> $Time
#> 107 164 66 133 136 14 70 42 70.1 184 24 168 56
#> 11.18 23.60 22.13 14.65 21.83 12.89 7.38 12.43 7.38 17.77 23.89 23.72 12.21
#> 43 106 168.1 192 128 23 171 111 60 8 63 29 129
#> 12.10 16.67 23.72 16.44 20.35 16.92 16.57 17.45 13.15 18.43 22.77 15.45 23.41
#> 6 45 127 108 106.1 136.1 133.1 88 134 18 155 190 177
#> 15.64 17.42 3.53 18.29 16.67 21.83 14.65 18.37 17.81 15.21 13.08 20.81 12.53
#> 16 128.1 43.1 105 14.1 14.2 139 93 6.1 85 192.1 6.2 26
#> 8.71 20.35 12.10 19.75 12.89 12.89 21.49 10.33 15.64 16.44 16.44 15.64 15.77
#> 15 60.1 57 194 10 42.1 167 133.2 192.2 128.2 40 43.2 123
#> 22.68 13.15 14.46 22.40 10.53 12.43 15.55 14.65 16.44 20.35 18.00 12.10 13.00
#> 158 81 117 184.1 29.1 170 169 101 169.1 14.3 175 127.1 39
#> 20.14 14.06 17.46 17.77 15.45 19.54 22.41 9.97 22.41 12.89 21.91 3.53 15.59
#> 86 42.2 164.1 16.1 86.1 168.2 100 76 25 106.2 153 175.1 93.1
#> 23.81 12.43 23.60 8.71 23.81 23.72 16.07 19.22 6.32 16.67 21.33 21.91 10.33
#> 8.1 70.2 61 108.1 150 51 41 197 168.3 181 106.3 52 68
#> 18.43 7.38 10.12 18.29 20.33 18.23 18.02 21.60 23.72 16.46 16.67 10.42 20.62
#> 137 33 119 11 143 200 193 64 2 104 35 2.1 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 162 137.1 20 80 161 165 160 138 94 17 12 35.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 17.1 34 135 21 146 126 147 151 121 62 31 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.1 118 174.1 132 46 94.1 74 28 122 132.1 11.1 21.1 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 87 196 142 165.1 146.1 182 12.1 143.2 80.1 156 193.1 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.1 19.1 98 160.2 178 75 103 95 142.1 34.1 182.1 172 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 54 82 196.1 72 103.1 178.1 161.1 34.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[34]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002334653 1.110118494 0.617685523
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.642360279 -0.002490923 -0.417280931
#> grade_iii, Cure model
#> -0.556901945
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 167 15.55 1 56 1 0
#> 14 12.89 1 21 0 0
#> 145 10.07 1 65 1 0
#> 177 12.53 1 75 0 0
#> 40 18.00 1 28 1 0
#> 181 16.46 1 45 0 1
#> 5 16.43 1 51 0 1
#> 52 10.42 1 52 0 1
#> 125 15.65 1 67 1 0
#> 37 12.52 1 57 1 0
#> 140 12.68 1 59 1 0
#> 179 18.63 1 42 0 0
#> 101 9.97 1 10 0 1
#> 91 5.33 1 61 0 1
#> 58 19.34 1 39 0 0
#> 187 9.92 1 39 1 0
#> 140.1 12.68 1 59 1 0
#> 45 17.42 1 54 0 1
#> 92 22.92 1 47 0 1
#> 107 11.18 1 54 1 0
#> 18 15.21 1 49 1 0
#> 189 10.51 1 NA 1 0
#> 107.1 11.18 1 54 1 0
#> 42 12.43 1 49 0 1
#> 92.1 22.92 1 47 0 1
#> 61 10.12 1 36 0 1
#> 89 11.44 1 NA 0 0
#> 184 17.77 1 38 0 0
#> 26 15.77 1 49 0 1
#> 129 23.41 1 53 1 0
#> 155 13.08 1 26 0 0
#> 69 23.23 1 25 0 1
#> 145.1 10.07 1 65 1 0
#> 168 23.72 1 70 0 0
#> 117 17.46 1 26 0 1
#> 155.1 13.08 1 26 0 0
#> 99 21.19 1 38 0 1
#> 61.1 10.12 1 36 0 1
#> 13 14.34 1 54 0 1
#> 175 21.91 1 43 0 0
#> 123 13.00 1 44 1 0
#> 188 16.16 1 46 0 1
#> 77 7.27 1 67 0 1
#> 8 18.43 1 32 0 0
#> 166 19.98 1 48 0 0
#> 96 14.54 1 33 0 1
#> 43 12.10 1 61 0 1
#> 43.1 12.10 1 61 0 1
#> 168.1 23.72 1 70 0 0
#> 114 13.68 1 NA 0 0
#> 189.1 10.51 1 NA 1 0
#> 89.1 11.44 1 NA 0 0
#> 58.1 19.34 1 39 0 0
#> 168.2 23.72 1 70 0 0
#> 66 22.13 1 53 0 0
#> 149 8.37 1 33 1 0
#> 36 21.19 1 48 0 1
#> 85 16.44 1 36 0 0
#> 171 16.57 1 41 0 1
#> 29 15.45 1 68 1 0
#> 188.1 16.16 1 46 0 1
#> 90 20.94 1 50 0 1
#> 78 23.88 1 43 0 0
#> 123.1 13.00 1 44 1 0
#> 5.1 16.43 1 51 0 1
#> 99.1 21.19 1 38 0 1
#> 99.2 21.19 1 38 0 1
#> 24 23.89 1 38 0 0
#> 24.1 23.89 1 38 0 0
#> 129.1 23.41 1 53 1 0
#> 76 19.22 1 54 0 1
#> 124 9.73 1 NA 1 0
#> 187.1 9.92 1 39 1 0
#> 181.1 16.46 1 45 0 1
#> 106 16.67 1 49 1 0
#> 85.1 16.44 1 36 0 0
#> 88 18.37 1 47 0 0
#> 154 12.63 1 20 1 0
#> 96.1 14.54 1 33 0 1
#> 167.1 15.55 1 56 1 0
#> 86 23.81 1 58 0 1
#> 153 21.33 1 55 1 0
#> 190 20.81 1 42 1 0
#> 37.1 12.52 1 57 1 0
#> 14.1 12.89 1 21 0 0
#> 13.1 14.34 1 54 0 1
#> 70 7.38 1 30 1 0
#> 60 13.15 1 38 1 0
#> 175.1 21.91 1 43 0 0
#> 114.1 13.68 1 NA 0 0
#> 24.2 23.89 1 38 0 0
#> 180 14.82 1 37 0 0
#> 175.2 21.91 1 43 0 0
#> 150 20.33 1 48 0 0
#> 184.1 17.77 1 38 0 0
#> 195 11.76 1 NA 1 0
#> 29.1 15.45 1 68 1 0
#> 58.2 19.34 1 39 0 0
#> 184.2 17.77 1 38 0 0
#> 14.2 12.89 1 21 0 0
#> 60.1 13.15 1 38 1 0
#> 78.1 23.88 1 43 0 0
#> 180.1 14.82 1 37 0 0
#> 180.2 14.82 1 37 0 0
#> 30 17.43 1 78 0 0
#> 24.3 23.89 1 38 0 0
#> 133 14.65 1 57 0 0
#> 42.1 12.43 1 49 0 1
#> 100 16.07 1 60 0 0
#> 194 22.40 1 38 0 1
#> 107.2 11.18 1 54 1 0
#> 177.1 12.53 1 75 0 0
#> 19 24.00 0 57 0 1
#> 84 24.00 0 39 0 1
#> 141 24.00 0 44 1 0
#> 47 24.00 0 38 0 1
#> 94 24.00 0 51 0 1
#> 95 24.00 0 68 0 1
#> 53 24.00 0 32 0 1
#> 137 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 94.1 24.00 0 51 0 1
#> 185 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 47.1 24.00 0 38 0 1
#> 54 24.00 0 53 1 0
#> 116 24.00 0 58 0 1
#> 44 24.00 0 56 0 0
#> 53.1 24.00 0 32 0 1
#> 196 24.00 0 19 0 0
#> 132 24.00 0 55 0 0
#> 104 24.00 0 50 1 0
#> 11 24.00 0 42 0 1
#> 115 24.00 0 NA 1 0
#> 74 24.00 0 43 0 1
#> 53.2 24.00 0 32 0 1
#> 137.1 24.00 0 45 1 0
#> 53.3 24.00 0 32 0 1
#> 151 24.00 0 42 0 0
#> 148 24.00 0 61 1 0
#> 186 24.00 0 45 1 0
#> 163.1 24.00 0 66 0 0
#> 200 24.00 0 64 0 0
#> 174 24.00 0 49 1 0
#> 161 24.00 0 45 0 0
#> 186.1 24.00 0 45 1 0
#> 200.1 24.00 0 64 0 0
#> 152 24.00 0 36 0 1
#> 142 24.00 0 53 0 0
#> 141.1 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 3 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 131 24.00 0 66 0 0
#> 185.1 24.00 0 44 1 0
#> 132.1 24.00 0 55 0 0
#> 120 24.00 0 68 0 1
#> 11.1 24.00 0 42 0 1
#> 116.1 24.00 0 58 0 1
#> 174.1 24.00 0 49 1 0
#> 74.1 24.00 0 43 0 1
#> 104.1 24.00 0 50 1 0
#> 47.2 24.00 0 38 0 1
#> 176 24.00 0 43 0 1
#> 156 24.00 0 50 1 0
#> 72 24.00 0 40 0 1
#> 185.2 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 176.1 24.00 0 43 0 1
#> 67 24.00 0 25 0 0
#> 1 24.00 0 23 1 0
#> 132.2 24.00 0 55 0 0
#> 144 24.00 0 28 0 1
#> 84.1 24.00 0 39 0 1
#> 118 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 120.1 24.00 0 68 0 1
#> 146 24.00 0 63 1 0
#> 116.2 24.00 0 58 0 1
#> 12 24.00 0 63 0 0
#> 31 24.00 0 36 0 1
#> 112 24.00 0 61 0 0
#> 103 24.00 0 56 1 0
#> 152.1 24.00 0 36 0 1
#> 143 24.00 0 51 0 0
#> 31.1 24.00 0 36 0 1
#> 142.1 24.00 0 53 0 0
#> 94.2 24.00 0 51 0 1
#> 83 24.00 0 6 0 0
#> 35 24.00 0 51 0 0
#> 198 24.00 0 66 0 1
#> 72.1 24.00 0 40 0 1
#> 118.1 24.00 0 44 1 0
#> 174.2 24.00 0 49 1 0
#> 75 24.00 0 21 1 0
#> 87 24.00 0 27 0 0
#> 20 24.00 0 46 1 0
#> 47.3 24.00 0 38 0 1
#> 73 24.00 0 NA 0 1
#> 95.1 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.642 NA NA NA
#> 2 age, Cure model -0.00249 NA NA NA
#> 3 grade_ii, Cure model -0.417 NA NA NA
#> 4 grade_iii, Cure model -0.557 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00233 NA NA NA
#> 2 grade_ii, Survival model 1.11 NA NA NA
#> 3 grade_iii, Survival model 0.618 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.642360 -0.002491 -0.417281 -0.556902
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 259 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.642360279 -0.002490923 -0.417280931 -0.556901945
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002334653 1.110118494 0.617685523
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.67360370 0.81635768 0.94726472 0.85766744 0.49127989 0.57721515
#> [7] 0.61298925 0.92876810 0.66515156 0.87113446 0.83728755 0.46100224
#> [13] 0.95929315 0.99429189 0.42103864 0.96529568 0.83728755 0.54915222
#> [19] 0.24027302 0.91016044 0.70528465 0.91016044 0.88426522 0.24027302
#> [25] 0.93498568 0.50102280 0.65652455 0.19809317 0.78792739 0.22634763
#> [31] 0.94726472 0.14510126 0.52982713 0.78792739 0.33880278 0.93498568
#> [37] 0.75859657 0.29046646 0.80236138 0.63056610 0.98856378 0.47107708
#> [43] 0.41088764 0.74349571 0.89726967 0.89726967 0.14510126 0.42103864
#> [49] 0.14510126 0.27792343 0.97700636 0.33880278 0.59508051 0.56802020
#> [55] 0.68973313 0.63056610 0.38008963 0.08741785 0.80236138 0.61298925
#> [61] 0.33880278 0.33880278 0.02930999 0.02930999 0.19809317 0.45094792
#> [67] 0.96529568 0.57721515 0.55872211 0.59508051 0.48116746 0.85092437
#> [73] 0.74349571 0.67360370 0.12601124 0.32693137 0.39066574 0.87113446
#> [79] 0.81635768 0.75859657 0.98281615 0.77350895 0.29046646 0.02930999
#> [85] 0.71295856 0.29046646 0.40076316 0.50102280 0.68973313 0.42103864
#> [91] 0.50102280 0.81635768 0.77350895 0.08741785 0.71295856 0.71295856
#> [97] 0.53947527 0.02930999 0.73579380 0.88426522 0.64782273 0.26544603
#> [103] 0.91016044 0.85766744 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 167 14 145 177 40 181 5 52 125 37 140 179 101
#> 15.55 12.89 10.07 12.53 18.00 16.46 16.43 10.42 15.65 12.52 12.68 18.63 9.97
#> 91 58 187 140.1 45 92 107 18 107.1 42 92.1 61 184
#> 5.33 19.34 9.92 12.68 17.42 22.92 11.18 15.21 11.18 12.43 22.92 10.12 17.77
#> 26 129 155 69 145.1 168 117 155.1 99 61.1 13 175 123
#> 15.77 23.41 13.08 23.23 10.07 23.72 17.46 13.08 21.19 10.12 14.34 21.91 13.00
#> 188 77 8 166 96 43 43.1 168.1 58.1 168.2 66 149 36
#> 16.16 7.27 18.43 19.98 14.54 12.10 12.10 23.72 19.34 23.72 22.13 8.37 21.19
#> 85 171 29 188.1 90 78 123.1 5.1 99.1 99.2 24 24.1 129.1
#> 16.44 16.57 15.45 16.16 20.94 23.88 13.00 16.43 21.19 21.19 23.89 23.89 23.41
#> 76 187.1 181.1 106 85.1 88 154 96.1 167.1 86 153 190 37.1
#> 19.22 9.92 16.46 16.67 16.44 18.37 12.63 14.54 15.55 23.81 21.33 20.81 12.52
#> 14.1 13.1 70 60 175.1 24.2 180 175.2 150 184.1 29.1 58.2 184.2
#> 12.89 14.34 7.38 13.15 21.91 23.89 14.82 21.91 20.33 17.77 15.45 19.34 17.77
#> 14.2 60.1 78.1 180.1 180.2 30 24.3 133 42.1 100 194 107.2 177.1
#> 12.89 13.15 23.88 14.82 14.82 17.43 23.89 14.65 12.43 16.07 22.40 11.18 12.53
#> 19 84 141 47 94 95 53 137 163 94.1 185 160 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 116 44 53.1 196 132 104 11 74 53.2 137.1 53.3 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 186 163.1 200 174 161 186.1 200.1 152 142 141.1 191 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 131 185.1 132.1 120 11.1 116.1 174.1 74.1 104.1 47.2 176 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 185.2 80 176.1 67 1 132.2 144 84.1 118 182 120.1 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.2 12 31 112 103 152.1 143 31.1 142.1 94.2 83 35 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 118.1 174.2 75 87 20 47.3 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[35]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.004676042 0.512377052 0.424486723
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.96975241 0.01361835 0.23788035
#> grade_iii, Cure model
#> 1.28499220
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 159 10.55 1 50 0 1
#> 15 22.68 1 48 0 0
#> 51 18.23 1 83 0 1
#> 164 23.60 1 76 0 1
#> 159.1 10.55 1 50 0 1
#> 16 8.71 1 71 0 1
#> 55 19.34 1 69 0 1
#> 114 13.68 1 NA 0 0
#> 69 23.23 1 25 0 1
#> 183 9.24 1 67 1 0
#> 63 22.77 1 31 1 0
#> 136 21.83 1 43 0 1
#> 167 15.55 1 56 1 0
#> 23 16.92 1 61 0 0
#> 43 12.10 1 61 0 1
#> 189 10.51 1 NA 1 0
#> 77 7.27 1 67 0 1
#> 29 15.45 1 68 1 0
#> 189.1 10.51 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 166 19.98 1 48 0 0
#> 55.1 19.34 1 69 0 1
#> 97 19.14 1 65 0 1
#> 52 10.42 1 52 0 1
#> 158 20.14 1 74 1 0
#> 167.1 15.55 1 56 1 0
#> 43.1 12.10 1 61 0 1
#> 155 13.08 1 26 0 0
#> 93 10.33 1 52 0 1
#> 114.1 13.68 1 NA 0 0
#> 117 17.46 1 26 0 1
#> 70 7.38 1 30 1 0
#> 194 22.40 1 38 0 1
#> 56 12.21 1 60 0 0
#> 159.2 10.55 1 50 0 1
#> 134 17.81 1 47 1 0
#> 197 21.60 1 69 1 0
#> 50 10.02 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 150 20.33 1 48 0 0
#> 127 3.53 1 62 0 1
#> 16.1 8.71 1 71 0 1
#> 14 12.89 1 21 0 0
#> 45 17.42 1 54 0 1
#> 78 23.88 1 43 0 0
#> 158.1 20.14 1 74 1 0
#> 23.1 16.92 1 61 0 0
#> 153 21.33 1 55 1 0
#> 192 16.44 1 31 1 0
#> 166.1 19.98 1 48 0 0
#> 159.3 10.55 1 50 0 1
#> 164.1 23.60 1 76 0 1
#> 14.1 12.89 1 21 0 0
#> 5 16.43 1 51 0 1
#> 6 15.64 1 39 0 0
#> 39 15.59 1 37 0 1
#> 29.1 15.45 1 68 1 0
#> 184 17.77 1 38 0 0
#> 140 12.68 1 59 1 0
#> 69.1 23.23 1 25 0 1
#> 129 23.41 1 53 1 0
#> 56.1 12.21 1 60 0 0
#> 91 5.33 1 61 0 1
#> 6.1 15.64 1 39 0 0
#> 195 11.76 1 NA 1 0
#> 154 12.63 1 20 1 0
#> 130 16.47 1 53 0 1
#> 6.2 15.64 1 39 0 0
#> 197.1 21.60 1 69 1 0
#> 78.1 23.88 1 43 0 0
#> 18 15.21 1 49 1 0
#> 52.1 10.42 1 52 0 1
#> 69.2 23.23 1 25 0 1
#> 166.2 19.98 1 48 0 0
#> 105 19.75 1 60 0 0
#> 145.1 10.07 1 65 1 0
#> 70.1 7.38 1 30 1 0
#> 166.3 19.98 1 48 0 0
#> 91.1 5.33 1 61 0 1
#> 63.1 22.77 1 31 1 0
#> 197.2 21.60 1 69 1 0
#> 101 9.97 1 10 0 1
#> 23.2 16.92 1 61 0 0
#> 194.1 22.40 1 38 0 1
#> 123 13.00 1 44 1 0
#> 14.2 12.89 1 21 0 0
#> 136.1 21.83 1 43 0 1
#> 59 10.16 1 NA 1 0
#> 97.1 19.14 1 65 0 1
#> 97.2 19.14 1 65 0 1
#> 188 16.16 1 46 0 1
#> 114.2 13.68 1 NA 0 0
#> 58 19.34 1 39 0 0
#> 55.2 19.34 1 69 0 1
#> 190 20.81 1 42 1 0
#> 50.1 10.02 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 199 19.81 1 NA 0 1
#> 96 14.54 1 33 0 1
#> 36 21.19 1 48 0 1
#> 183.1 9.24 1 67 1 0
#> 61 10.12 1 36 0 1
#> 183.2 9.24 1 67 1 0
#> 145.2 10.07 1 65 1 0
#> 24 23.89 1 38 0 0
#> 60 13.15 1 38 1 0
#> 26 15.77 1 49 0 1
#> 145.3 10.07 1 65 1 0
#> 39.1 15.59 1 37 0 1
#> 166.4 19.98 1 48 0 0
#> 24.1 23.89 1 38 0 0
#> 114.3 13.68 1 NA 0 0
#> 174 24.00 0 49 1 0
#> 138 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 142 24.00 0 53 0 0
#> 80 24.00 0 41 0 0
#> 22 24.00 0 52 1 0
#> 161 24.00 0 45 0 0
#> 73 24.00 0 NA 0 1
#> 84 24.00 0 39 0 1
#> 141 24.00 0 44 1 0
#> 53 24.00 0 32 0 1
#> 47 24.00 0 38 0 1
#> 122 24.00 0 66 0 0
#> 27 24.00 0 63 1 0
#> 1 24.00 0 23 1 0
#> 161.1 24.00 0 45 0 0
#> 103 24.00 0 56 1 0
#> 19 24.00 0 57 0 1
#> 135 24.00 0 58 1 0
#> 112 24.00 0 61 0 0
#> 182 24.00 0 35 0 0
#> 27.1 24.00 0 63 1 0
#> 12 24.00 0 63 0 0
#> 67 24.00 0 25 0 0
#> 74 24.00 0 43 0 1
#> 174.1 24.00 0 49 1 0
#> 54 24.00 0 53 1 0
#> 138.1 24.00 0 44 1 0
#> 80.1 24.00 0 41 0 0
#> 7 24.00 0 37 1 0
#> 20 24.00 0 46 1 0
#> 87 24.00 0 27 0 0
#> 20.1 24.00 0 46 1 0
#> 131 24.00 0 66 0 0
#> 22.1 24.00 0 52 1 0
#> 121 24.00 0 57 1 0
#> 82 24.00 0 34 0 0
#> 67.1 24.00 0 25 0 0
#> 33 24.00 0 53 0 0
#> 44 24.00 0 56 0 0
#> 162 24.00 0 51 0 0
#> 72 24.00 0 40 0 1
#> 109 24.00 0 48 0 0
#> 142.1 24.00 0 53 0 0
#> 182.1 24.00 0 35 0 0
#> 112.1 24.00 0 61 0 0
#> 173 24.00 0 19 0 1
#> 84.1 24.00 0 39 0 1
#> 120 24.00 0 68 0 1
#> 144 24.00 0 28 0 1
#> 148 24.00 0 61 1 0
#> 33.1 24.00 0 53 0 0
#> 137 24.00 0 45 1 0
#> 185 24.00 0 44 1 0
#> 135.1 24.00 0 58 1 0
#> 46 24.00 0 71 0 0
#> 121.1 24.00 0 57 1 0
#> 116 24.00 0 58 0 1
#> 71 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 143 24.00 0 51 0 0
#> 121.2 24.00 0 57 1 0
#> 67.2 24.00 0 25 0 0
#> 74.1 24.00 0 43 0 1
#> 115.1 24.00 0 NA 1 0
#> 33.2 24.00 0 53 0 0
#> 178 24.00 0 52 1 0
#> 126.1 24.00 0 48 0 0
#> 115.2 24.00 0 NA 1 0
#> 11 24.00 0 42 0 1
#> 38 24.00 0 31 1 0
#> 141.1 24.00 0 44 1 0
#> 44.1 24.00 0 56 0 0
#> 116.1 24.00 0 58 0 1
#> 163 24.00 0 66 0 0
#> 19.1 24.00 0 57 0 1
#> 28 24.00 0 67 1 0
#> 151 24.00 0 42 0 0
#> 75 24.00 0 21 1 0
#> 65 24.00 0 57 1 0
#> 118 24.00 0 44 1 0
#> 33.3 24.00 0 53 0 0
#> 193 24.00 0 45 0 1
#> 3 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 173.1 24.00 0 19 0 1
#> 122.1 24.00 0 66 0 0
#> 200 24.00 0 64 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.970 NA NA NA
#> 2 age, Cure model 0.0136 NA NA NA
#> 3 grade_ii, Cure model 0.238 NA NA NA
#> 4 grade_iii, Cure model 1.28 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00468 NA NA NA
#> 2 grade_ii, Survival model 0.512 NA NA NA
#> 3 grade_iii, Survival model 0.424 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.96975 0.01362 0.23788 1.28499
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 254.9
#> Residual Deviance: 240.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.96975241 0.01361835 0.23788035 1.28499220
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.004676042 0.512377052 0.424486723
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.86157616 0.31286546 0.60666275 0.17414386 0.86157616 0.95605005
#> [7] 0.54847770 0.23641068 0.93914235 0.28357950 0.35469659 0.74250874
#> [13] 0.64642597 0.84892907 0.97824506 0.75644628 0.91024742 0.48487645
#> [19] 0.54847770 0.58227348 0.88602121 0.46583154 0.74250874 0.84892907
#> [25] 0.79022278 0.89816897 0.63072509 0.96720617 0.32768945 0.83608423
#> [31] 0.86157616 0.61476594 0.38002868 0.53931584 0.45563731 0.99459271
#> [37] 0.95605005 0.80348616 0.63862223 0.11514289 0.46583154 0.64642597
#> [43] 0.41314401 0.67691003 0.48487645 0.86157616 0.17414386 0.80348616
#> [49] 0.68445523 0.70664410 0.72825854 0.75644628 0.62275546 0.82308252
#> [55] 0.23641068 0.21644821 0.83608423 0.98374621 0.70664410 0.82960459
#> [61] 0.66928583 0.70664410 0.38002868 0.11514289 0.77005925 0.88602121
#> [67] 0.23641068 0.48487645 0.53001666 0.91024742 0.96720617 0.48487645
#> [73] 0.98374621 0.28357950 0.38002868 0.93333734 0.64642597 0.32768945
#> [79] 0.79688346 0.80348616 0.35469659 0.58227348 0.58227348 0.69192301
#> [85] 0.54847770 0.54847770 0.44538538 0.43488414 0.77683002 0.42414129
#> [91] 0.93914235 0.90422451 0.93914235 0.91024742 0.04984766 0.78355484
#> [97] 0.69931929 0.91024742 0.72825854 0.48487645 0.04984766 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 159 15 51 164 159.1 16 55 69 183 63 136 167 23
#> 10.55 22.68 18.23 23.60 10.55 8.71 19.34 23.23 9.24 22.77 21.83 15.55 16.92
#> 43 77 29 145 166 55.1 97 52 158 167.1 43.1 155 93
#> 12.10 7.27 15.45 10.07 19.98 19.34 19.14 10.42 20.14 15.55 12.10 13.08 10.33
#> 117 70 194 56 159.2 134 197 170 150 127 16.1 14 45
#> 17.46 7.38 22.40 12.21 10.55 17.81 21.60 19.54 20.33 3.53 8.71 12.89 17.42
#> 78 158.1 23.1 153 192 166.1 159.3 164.1 14.1 5 6 39 29.1
#> 23.88 20.14 16.92 21.33 16.44 19.98 10.55 23.60 12.89 16.43 15.64 15.59 15.45
#> 184 140 69.1 129 56.1 91 6.1 154 130 6.2 197.1 78.1 18
#> 17.77 12.68 23.23 23.41 12.21 5.33 15.64 12.63 16.47 15.64 21.60 23.88 15.21
#> 52.1 69.2 166.2 105 145.1 70.1 166.3 91.1 63.1 197.2 101 23.2 194.1
#> 10.42 23.23 19.98 19.75 10.07 7.38 19.98 5.33 22.77 21.60 9.97 16.92 22.40
#> 123 14.2 136.1 97.1 97.2 188 58 55.2 190 90 96 36 183.1
#> 13.00 12.89 21.83 19.14 19.14 16.16 19.34 19.34 20.81 20.94 14.54 21.19 9.24
#> 61 183.2 145.2 24 60 26 145.3 39.1 166.4 24.1 174 138 142
#> 10.12 9.24 10.07 23.89 13.15 15.77 10.07 15.59 19.98 23.89 24.00 24.00 24.00
#> 80 22 161 84 141 53 47 122 27 1 161.1 103 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 112 182 27.1 12 67 74 174.1 54 138.1 80.1 7 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 20.1 131 22.1 121 82 67.1 33 44 162 72 109 142.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.1 112.1 173 84.1 120 144 148 33.1 137 185 135.1 46 121.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 71 126 143 121.2 67.2 74.1 33.2 178 126.1 11 38 141.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44.1 116.1 163 19.1 28 151 75 65 118 33.3 193 3 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173.1 122.1 200
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[36]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001692444 0.904819253 0.454362278
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.664645448 0.006445945 0.410016750
#> grade_iii, Cure model
#> 1.180214794
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 23 16.92 1 61 0 0
#> 81 14.06 1 34 0 0
#> 97 19.14 1 65 0 1
#> 194 22.40 1 38 0 1
#> 78 23.88 1 43 0 0
#> 68 20.62 1 44 0 0
#> 150 20.33 1 48 0 0
#> 167 15.55 1 56 1 0
#> 130 16.47 1 53 0 1
#> 114 13.68 1 NA 0 0
#> 111 17.45 1 47 0 1
#> 15 22.68 1 48 0 0
#> 76 19.22 1 54 0 1
#> 88 18.37 1 47 0 0
#> 166 19.98 1 48 0 0
#> 150.1 20.33 1 48 0 0
#> 106 16.67 1 49 1 0
#> 6 15.64 1 39 0 0
#> 96 14.54 1 33 0 1
#> 43 12.10 1 61 0 1
#> 41 18.02 1 40 1 0
#> 39 15.59 1 37 0 1
#> 43.1 12.10 1 61 0 1
#> 140 12.68 1 59 1 0
#> 25 6.32 1 34 1 0
#> 125 15.65 1 67 1 0
#> 114.1 13.68 1 NA 0 0
#> 189 10.51 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 189.1 10.51 1 NA 1 0
#> 5 16.43 1 51 0 1
#> 36 21.19 1 48 0 1
#> 194.1 22.40 1 38 0 1
#> 42 12.43 1 49 0 1
#> 43.2 12.10 1 61 0 1
#> 199.1 19.81 1 NA 0 1
#> 101 9.97 1 10 0 1
#> 171 16.57 1 41 0 1
#> 40 18.00 1 28 1 0
#> 168 23.72 1 70 0 0
#> 190 20.81 1 42 1 0
#> 195 11.76 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 189.2 10.51 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 177 12.53 1 75 0 0
#> 123 13.00 1 44 1 0
#> 114.2 13.68 1 NA 0 0
#> 140.1 12.68 1 59 1 0
#> 153 21.33 1 55 1 0
#> 110 17.56 1 65 0 1
#> 108 18.29 1 39 0 1
#> 154 12.63 1 20 1 0
#> 180 14.82 1 37 0 0
#> 52 10.42 1 52 0 1
#> 36.1 21.19 1 48 0 1
#> 183 9.24 1 67 1 0
#> 128 20.35 1 35 0 1
#> 43.3 12.10 1 61 0 1
#> 85 16.44 1 36 0 0
#> 175 21.91 1 43 0 0
#> 40.1 18.00 1 28 1 0
#> 89 11.44 1 NA 0 0
#> 97.1 19.14 1 65 0 1
#> 40.2 18.00 1 28 1 0
#> 32 20.90 1 37 1 0
#> 105 19.75 1 60 0 0
#> 171.1 16.57 1 41 0 1
#> 43.4 12.10 1 61 0 1
#> 195.1 11.76 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 69 23.23 1 25 0 1
#> 37 12.52 1 57 1 0
#> 189.3 10.51 1 NA 1 0
#> 15.1 22.68 1 48 0 0
#> 123.1 13.00 1 44 1 0
#> 111.1 17.45 1 47 0 1
#> 110.1 17.56 1 65 0 1
#> 99 21.19 1 38 0 1
#> 23.1 16.92 1 61 0 0
#> 70 7.38 1 30 1 0
#> 66 22.13 1 53 0 0
#> 164 23.60 1 76 0 1
#> 154.1 12.63 1 20 1 0
#> 179 18.63 1 42 0 0
#> 188 16.16 1 46 0 1
#> 159 10.55 1 50 0 1
#> 79 16.23 1 54 1 0
#> 168.1 23.72 1 70 0 0
#> 40.3 18.00 1 28 1 0
#> 56 12.21 1 60 0 0
#> 6.1 15.64 1 39 0 0
#> 157 15.10 1 47 0 0
#> 113 22.86 1 34 0 0
#> 192 16.44 1 31 1 0
#> 88.1 18.37 1 47 0 0
#> 85.1 16.44 1 36 0 0
#> 164.1 23.60 1 76 0 1
#> 97.2 19.14 1 65 0 1
#> 100 16.07 1 60 0 0
#> 39.1 15.59 1 37 0 1
#> 158 20.14 1 74 1 0
#> 77 7.27 1 67 0 1
#> 93 10.33 1 52 0 1
#> 99.1 21.19 1 38 0 1
#> 36.2 21.19 1 48 0 1
#> 110.2 17.56 1 65 0 1
#> 79.1 16.23 1 54 1 0
#> 145 10.07 1 65 1 0
#> 130.1 16.47 1 53 0 1
#> 93.1 10.33 1 52 0 1
#> 194.2 22.40 1 38 0 1
#> 21 24.00 0 47 0 0
#> 35 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 73 24.00 0 NA 0 1
#> 47.1 24.00 0 38 0 1
#> 191 24.00 0 60 0 1
#> 21.1 24.00 0 47 0 0
#> 87 24.00 0 27 0 0
#> 182 24.00 0 35 0 0
#> 102 24.00 0 49 0 0
#> 7 24.00 0 37 1 0
#> 27 24.00 0 63 1 0
#> 173 24.00 0 19 0 1
#> 3 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 165 24.00 0 47 0 0
#> 73.1 24.00 0 NA 0 1
#> 74 24.00 0 43 0 1
#> 28 24.00 0 67 1 0
#> 178 24.00 0 52 1 0
#> 1 24.00 0 23 1 0
#> 74.1 24.00 0 43 0 1
#> 163 24.00 0 66 0 0
#> 148 24.00 0 61 1 0
#> 17 24.00 0 38 0 1
#> 82 24.00 0 34 0 0
#> 82.1 24.00 0 34 0 0
#> 142 24.00 0 53 0 0
#> 33.1 24.00 0 53 0 0
#> 148.1 24.00 0 61 1 0
#> 151 24.00 0 42 0 0
#> 38 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 12 24.00 0 63 0 0
#> 196 24.00 0 19 0 0
#> 191.1 24.00 0 60 0 1
#> 46 24.00 0 71 0 0
#> 163.1 24.00 0 66 0 0
#> 28.1 24.00 0 67 1 0
#> 120 24.00 0 68 0 1
#> 80 24.00 0 41 0 0
#> 162 24.00 0 51 0 0
#> 182.1 24.00 0 35 0 0
#> 62 24.00 0 71 0 0
#> 1.1 24.00 0 23 1 0
#> 141 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 82.2 24.00 0 34 0 0
#> 35.1 24.00 0 51 0 0
#> 80.1 24.00 0 41 0 0
#> 19 24.00 0 57 0 1
#> 126 24.00 0 48 0 0
#> 115 24.00 0 NA 1 0
#> 19.1 24.00 0 57 0 1
#> 87.1 24.00 0 27 0 0
#> 147 24.00 0 76 1 0
#> 191.2 24.00 0 60 0 1
#> 160 24.00 0 31 1 0
#> 7.1 24.00 0 37 1 0
#> 112 24.00 0 61 0 0
#> 62.1 24.00 0 71 0 0
#> 147.1 24.00 0 76 1 0
#> 151.1 24.00 0 42 0 0
#> 151.2 24.00 0 42 0 0
#> 9.1 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 62.2 24.00 0 71 0 0
#> 94 24.00 0 51 0 1
#> 176 24.00 0 43 0 1
#> 74.2 24.00 0 43 0 1
#> 119 24.00 0 17 0 0
#> 27.1 24.00 0 63 1 0
#> 72 24.00 0 40 0 1
#> 12.1 24.00 0 63 0 0
#> 94.1 24.00 0 51 0 1
#> 2 24.00 0 9 0 0
#> 11 24.00 0 42 0 1
#> 82.3 24.00 0 34 0 0
#> 20 24.00 0 46 1 0
#> 46.1 24.00 0 71 0 0
#> 120.1 24.00 0 68 0 1
#> 7.2 24.00 0 37 1 0
#> 147.2 24.00 0 76 1 0
#> 83 24.00 0 6 0 0
#> 132 24.00 0 55 0 0
#> 75.1 24.00 0 21 1 0
#> 104 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.665 NA NA NA
#> 2 age, Cure model 0.00645 NA NA NA
#> 3 grade_ii, Cure model 0.410 NA NA NA
#> 4 grade_iii, Cure model 1.18 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00169 NA NA NA
#> 2 grade_ii, Survival model 0.905 NA NA NA
#> 3 grade_iii, Survival model 0.454 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.664645 0.006446 0.410017 1.180215
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.2
#> Residual Deviance: 243.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.664645448 0.006445945 0.410016750 1.180214794
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001692444 0.904819253 0.454362278
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.60027665 0.81166700 0.43770265 0.18083659 0.01273125 0.34930863
#> [7] 0.37191806 0.77307580 0.64371167 0.58270105 0.14737463 0.42687863
#> [13] 0.47896765 0.40501549 0.37191806 0.61790290 0.74175940 0.79628879
#> [19] 0.89151590 0.51024211 0.75749520 0.89151590 0.83426378 0.98685929
#> [25] 0.73386009 0.68539809 0.26823533 0.18083659 0.87737652 0.89151590
#> [31] 0.96006976 0.62662015 0.52039950 0.03732071 0.33794472 0.80399479
#> [37] 0.72585684 0.86311855 0.81934326 0.83426378 0.25397201 0.55617655
#> [43] 0.49981282 0.84886146 0.78854610 0.93268826 0.26823533 0.96684532
#> [49] 0.36069916 0.89151590 0.66060584 0.23863069 0.52039950 0.43770265
#> [55] 0.52039950 0.32606064 0.41593318 0.62662015 0.89151590 0.99343873
#> [61] 0.11258923 0.87028387 0.14737463 0.81934326 0.58270105 0.55617655
#> [67] 0.26823533 0.60027665 0.97356407 0.22335861 0.07814351 0.84886146
#> [73] 0.46846454 0.70977926 0.92575923 0.69371868 0.03732071 0.52039950
#> [79] 0.88444349 0.74175940 0.78080802 0.12991518 0.66060584 0.47896765
#> [85] 0.66060584 0.07814351 0.43770265 0.71781371 0.75749520 0.39412073
#> [91] 0.98022084 0.93959458 0.26823533 0.26823533 0.55617655 0.69371868
#> [97] 0.95326786 0.64371167 0.93959458 0.18083659 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 23 81 97 194 78 68 150 167 130 111 15 76 88
#> 16.92 14.06 19.14 22.40 23.88 20.62 20.33 15.55 16.47 17.45 22.68 19.22 18.37
#> 166 150.1 106 6 96 43 41 39 43.1 140 25 125 5
#> 19.98 20.33 16.67 15.64 14.54 12.10 18.02 15.59 12.10 12.68 6.32 15.65 16.43
#> 36 194.1 42 43.2 101 171 40 168 190 57 26 177 123
#> 21.19 22.40 12.43 12.10 9.97 16.57 18.00 23.72 20.81 14.46 15.77 12.53 13.00
#> 140.1 153 110 108 154 180 52 36.1 183 128 43.3 85 175
#> 12.68 21.33 17.56 18.29 12.63 14.82 10.42 21.19 9.24 20.35 12.10 16.44 21.91
#> 40.1 97.1 40.2 32 105 171.1 43.4 127 69 37 15.1 123.1 111.1
#> 18.00 19.14 18.00 20.90 19.75 16.57 12.10 3.53 23.23 12.52 22.68 13.00 17.45
#> 110.1 99 23.1 70 66 164 154.1 179 188 159 79 168.1 40.3
#> 17.56 21.19 16.92 7.38 22.13 23.60 12.63 18.63 16.16 10.55 16.23 23.72 18.00
#> 56 6.1 157 113 192 88.1 85.1 164.1 97.2 100 39.1 158 77
#> 12.21 15.64 15.10 22.86 16.44 18.37 16.44 23.60 19.14 16.07 15.59 20.14 7.27
#> 93 99.1 36.2 110.2 79.1 145 130.1 93.1 194.2 21 35 9 47
#> 10.33 21.19 21.19 17.56 16.23 10.07 16.47 10.33 22.40 24.00 24.00 24.00 24.00
#> 47.1 191 21.1 87 182 102 7 27 173 3 33 165 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 178 1 74.1 163 148 17 82 82.1 142 33.1 148.1 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 75 12 196 191.1 46 163.1 28.1 120 80 162 182.1 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.1 141 200 82.2 35.1 80.1 19 126 19.1 87.1 147 191.2 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.1 112 62.1 147.1 151.1 151.2 9.1 152 62.2 94 176 74.2 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27.1 72 12.1 94.1 2 11 82.3 20 46.1 120.1 7.2 147.2 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 75.1 104
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[37]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01228701 0.38950704 0.48309193
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.143370438 -0.005598245 0.407908925
#> grade_iii, Cure model
#> 0.529795870
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 32 20.90 1 37 1 0
#> 93 10.33 1 52 0 1
#> 97 19.14 1 65 0 1
#> 100 16.07 1 60 0 0
#> 159 10.55 1 50 0 1
#> 179 18.63 1 42 0 0
#> 24 23.89 1 38 0 0
#> 114 13.68 1 NA 0 0
#> 111 17.45 1 47 0 1
#> 179.1 18.63 1 42 0 0
#> 49 12.19 1 48 1 0
#> 192 16.44 1 31 1 0
#> 134 17.81 1 47 1 0
#> 77 7.27 1 67 0 1
#> 100.1 16.07 1 60 0 0
#> 13 14.34 1 54 0 1
#> 166 19.98 1 48 0 0
#> 24.1 23.89 1 38 0 0
#> 99 21.19 1 38 0 1
#> 134.1 17.81 1 47 1 0
#> 190 20.81 1 42 1 0
#> 15 22.68 1 48 0 0
#> 14 12.89 1 21 0 0
#> 5 16.43 1 51 0 1
#> 166.1 19.98 1 48 0 0
#> 25 6.32 1 34 1 0
#> 39 15.59 1 37 0 1
#> 39.1 15.59 1 37 0 1
#> 130 16.47 1 53 0 1
#> 190.1 20.81 1 42 1 0
#> 149 8.37 1 33 1 0
#> 113 22.86 1 34 0 0
#> 92 22.92 1 47 0 1
#> 52 10.42 1 52 0 1
#> 114.1 13.68 1 NA 0 0
#> 158 20.14 1 74 1 0
#> 171 16.57 1 41 0 1
#> 59 10.16 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 154 12.63 1 20 1 0
#> 199 19.81 1 NA 0 1
#> 107 11.18 1 54 1 0
#> 85 16.44 1 36 0 0
#> 16 8.71 1 71 0 1
#> 105 19.75 1 60 0 0
#> 37 12.52 1 57 1 0
#> 52.1 10.42 1 52 0 1
#> 23 16.92 1 61 0 0
#> 107.1 11.18 1 54 1 0
#> 69 23.23 1 25 0 1
#> 86 23.81 1 58 0 1
#> 99.1 21.19 1 38 0 1
#> 190.2 20.81 1 42 1 0
#> 150.1 20.33 1 48 0 0
#> 184 17.77 1 38 0 0
#> 85.1 16.44 1 36 0 0
#> 39.2 15.59 1 37 0 1
#> 197 21.60 1 69 1 0
#> 150.2 20.33 1 48 0 0
#> 45 17.42 1 54 0 1
#> 192.1 16.44 1 31 1 0
#> 139 21.49 1 63 1 0
#> 63 22.77 1 31 1 0
#> 41 18.02 1 40 1 0
#> 32.1 20.90 1 37 1 0
#> 190.3 20.81 1 42 1 0
#> 154.1 12.63 1 20 1 0
#> 154.2 12.63 1 20 1 0
#> 59.1 10.16 1 NA 1 0
#> 77.1 7.27 1 67 0 1
#> 100.2 16.07 1 60 0 0
#> 14.1 12.89 1 21 0 0
#> 177 12.53 1 75 0 0
#> 100.3 16.07 1 60 0 0
#> 171.1 16.57 1 41 0 1
#> 181 16.46 1 45 0 1
#> 56 12.21 1 60 0 0
#> 93.1 10.33 1 52 0 1
#> 36 21.19 1 48 0 1
#> 58 19.34 1 39 0 0
#> 125 15.65 1 67 1 0
#> 140 12.68 1 59 1 0
#> 106 16.67 1 49 1 0
#> 159.1 10.55 1 50 0 1
#> 6 15.64 1 39 0 0
#> 189 10.51 1 NA 1 0
#> 189.1 10.51 1 NA 1 0
#> 70 7.38 1 30 1 0
#> 5.1 16.43 1 51 0 1
#> 175 21.91 1 43 0 0
#> 97.1 19.14 1 65 0 1
#> 184.1 17.77 1 38 0 0
#> 117 17.46 1 26 0 1
#> 32.2 20.90 1 37 1 0
#> 79 16.23 1 54 1 0
#> 128 20.35 1 35 0 1
#> 187 9.92 1 39 1 0
#> 184.2 17.77 1 38 0 0
#> 105.1 19.75 1 60 0 0
#> 181.1 16.46 1 45 0 1
#> 39.3 15.59 1 37 0 1
#> 23.1 16.92 1 61 0 0
#> 195 11.76 1 NA 1 0
#> 59.2 10.16 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 42 12.43 1 49 0 1
#> 199.1 19.81 1 NA 0 1
#> 78 23.88 1 43 0 0
#> 58.1 19.34 1 39 0 0
#> 18 15.21 1 49 1 0
#> 150.3 20.33 1 48 0 0
#> 171.2 16.57 1 41 0 1
#> 196 24.00 0 19 0 0
#> 109 24.00 0 48 0 0
#> 2 24.00 0 9 0 0
#> 84 24.00 0 39 0 1
#> 2.1 24.00 0 9 0 0
#> 72 24.00 0 40 0 1
#> 151 24.00 0 42 0 0
#> 163 24.00 0 66 0 0
#> 148 24.00 0 61 1 0
#> 82 24.00 0 34 0 0
#> 28 24.00 0 67 1 0
#> 165 24.00 0 47 0 0
#> 38 24.00 0 31 1 0
#> 2.2 24.00 0 9 0 0
#> 46 24.00 0 71 0 0
#> 80 24.00 0 41 0 0
#> 144 24.00 0 28 0 1
#> 62 24.00 0 71 0 0
#> 53 24.00 0 32 0 1
#> 95 24.00 0 68 0 1
#> 83 24.00 0 6 0 0
#> 143 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 17 24.00 0 38 0 1
#> 54 24.00 0 53 1 0
#> 135 24.00 0 58 1 0
#> 94 24.00 0 51 0 1
#> 73 24.00 0 NA 0 1
#> 116 24.00 0 58 0 1
#> 178 24.00 0 52 1 0
#> 109.1 24.00 0 48 0 0
#> 173 24.00 0 19 0 1
#> 137 24.00 0 45 1 0
#> 12 24.00 0 63 0 0
#> 141 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 116.1 24.00 0 58 0 1
#> 151.1 24.00 0 42 0 0
#> 62.1 24.00 0 71 0 0
#> 67 24.00 0 25 0 0
#> 143.1 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 22 24.00 0 52 1 0
#> 144.1 24.00 0 28 0 1
#> 172 24.00 0 41 0 0
#> 142 24.00 0 53 0 0
#> 72.1 24.00 0 40 0 1
#> 200 24.00 0 64 0 0
#> 65 24.00 0 57 1 0
#> 27 24.00 0 63 1 0
#> 152 24.00 0 36 0 1
#> 2.3 24.00 0 9 0 0
#> 131 24.00 0 66 0 0
#> 193 24.00 0 45 0 1
#> 27.1 24.00 0 63 1 0
#> 116.2 24.00 0 58 0 1
#> 191.1 24.00 0 60 0 1
#> 84.1 24.00 0 39 0 1
#> 54.1 24.00 0 53 1 0
#> 185 24.00 0 44 1 0
#> 156 24.00 0 50 1 0
#> 33 24.00 0 53 0 0
#> 71 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 163.1 24.00 0 66 0 0
#> 151.2 24.00 0 42 0 0
#> 109.2 24.00 0 48 0 0
#> 95.1 24.00 0 68 0 1
#> 7 24.00 0 37 1 0
#> 156.1 24.00 0 50 1 0
#> 147 24.00 0 76 1 0
#> 141.1 24.00 0 44 1 0
#> 193.1 24.00 0 45 0 1
#> 44 24.00 0 56 0 0
#> 95.2 24.00 0 68 0 1
#> 44.1 24.00 0 56 0 0
#> 62.2 24.00 0 71 0 0
#> 135.1 24.00 0 58 1 0
#> 22.1 24.00 0 52 1 0
#> 95.3 24.00 0 68 0 1
#> 2.4 24.00 0 9 0 0
#> 112 24.00 0 61 0 0
#> 31 24.00 0 36 0 1
#> 174 24.00 0 49 1 0
#> 112.1 24.00 0 61 0 0
#> 151.3 24.00 0 42 0 0
#> 73.1 24.00 0 NA 0 1
#> 11 24.00 0 42 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.143 NA NA NA
#> 2 age, Cure model -0.00560 NA NA NA
#> 3 grade_ii, Cure model 0.408 NA NA NA
#> 4 grade_iii, Cure model 0.530 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0123 NA NA NA
#> 2 grade_ii, Survival model 0.390 NA NA NA
#> 3 grade_iii, Survival model 0.483 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.143370 -0.005598 0.407909 0.529796
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 256.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.143370438 -0.005598245 0.407908925 0.529795870
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01228701 0.38950704 0.48309193
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.4531796 0.9585497 0.6295394 0.8177440 0.9410011 0.6447686 0.0993430
#> [8] 0.7092190 0.6447686 0.9273648 0.7783619 0.6671771 0.9838520 0.8177440
#> [15] 0.8745531 0.5797294 0.0993430 0.4161625 0.6671771 0.4865822 0.3473082
#> [22] 0.8795016 0.8011025 0.5797294 0.9919583 0.8494848 0.8494848 0.7605423
#> [29] 0.4865822 0.9755242 0.3060375 0.2838456 0.9498593 0.5709389 0.7421760
#> [36] 0.5351463 0.8942147 0.9319732 0.7783619 0.9713285 0.5967652 0.9133259
#> [43] 0.9498593 0.7227082 0.9319732 0.2578148 0.2281891 0.4161625 0.4865822
#> [50] 0.5351463 0.6814180 0.7783619 0.8494848 0.3846623 0.5351463 0.7160318
#> [57] 0.7783619 0.4010918 0.3274261 0.6597588 0.4531796 0.4865822 0.8942147
#> [64] 0.8942147 0.9838520 0.8177440 0.8795016 0.9085577 0.8177440 0.7421760
#> [71] 0.7666104 0.9227179 0.9585497 0.4161625 0.6132869 0.8389560 0.8893381
#> [78] 0.7357321 0.9410011 0.8442305 0.9796982 0.8011025 0.3663165 0.6295394
#> [85] 0.6814180 0.7022803 0.4531796 0.8122312 0.5254289 0.9670799 0.6814180
#> [92] 0.5967652 0.7666104 0.8494848 0.7227082 0.9959992 0.9180454 0.1859573
#> [99] 0.6132869 0.8695438 0.5351463 0.7421760 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 32 93 97 100 159 179 24 111 179.1 49 192 134 77
#> 20.90 10.33 19.14 16.07 10.55 18.63 23.89 17.45 18.63 12.19 16.44 17.81 7.27
#> 100.1 13 166 24.1 99 134.1 190 15 14 5 166.1 25 39
#> 16.07 14.34 19.98 23.89 21.19 17.81 20.81 22.68 12.89 16.43 19.98 6.32 15.59
#> 39.1 130 190.1 149 113 92 52 158 171 150 154 107 85
#> 15.59 16.47 20.81 8.37 22.86 22.92 10.42 20.14 16.57 20.33 12.63 11.18 16.44
#> 16 105 37 52.1 23 107.1 69 86 99.1 190.2 150.1 184 85.1
#> 8.71 19.75 12.52 10.42 16.92 11.18 23.23 23.81 21.19 20.81 20.33 17.77 16.44
#> 39.2 197 150.2 45 192.1 139 63 41 32.1 190.3 154.1 154.2 77.1
#> 15.59 21.60 20.33 17.42 16.44 21.49 22.77 18.02 20.90 20.81 12.63 12.63 7.27
#> 100.2 14.1 177 100.3 171.1 181 56 93.1 36 58 125 140 106
#> 16.07 12.89 12.53 16.07 16.57 16.46 12.21 10.33 21.19 19.34 15.65 12.68 16.67
#> 159.1 6 70 5.1 175 97.1 184.1 117 32.2 79 128 187 184.2
#> 10.55 15.64 7.38 16.43 21.91 19.14 17.77 17.46 20.90 16.23 20.35 9.92 17.77
#> 105.1 181.1 39.3 23.1 127 42 78 58.1 18 150.3 171.2 196 109
#> 19.75 16.46 15.59 16.92 3.53 12.43 23.88 19.34 15.21 20.33 16.57 24.00 24.00
#> 2 84 2.1 72 151 163 148 82 28 165 38 2.2 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 144 62 53 95 83 143 191 17 54 135 94 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 109.1 173 137 12 141 160 116.1 151.1 62.1 67 143.1 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 144.1 172 142 72.1 200 65 27 152 2.3 131 193 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.2 191.1 84.1 54.1 185 156 33 71 118 163.1 151.2 109.2 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 156.1 147 141.1 193.1 44 95.2 44.1 62.2 135.1 22.1 95.3 2.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 31 174 112.1 151.3 11
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[38]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0009598553 0.3844219906 0.3513257543
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.12711651 0.00219604 -0.21613550
#> grade_iii, Cure model
#> 1.07697161
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 49 12.19 1 48 1 0
#> 130 16.47 1 53 0 1
#> 187 9.92 1 39 1 0
#> 70 7.38 1 30 1 0
#> 125 15.65 1 67 1 0
#> 42 12.43 1 49 0 1
#> 189 10.51 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 43 12.10 1 61 0 1
#> 136 21.83 1 43 0 1
#> 77 7.27 1 67 0 1
#> 130.1 16.47 1 53 0 1
#> 150 20.33 1 48 0 0
#> 108 18.29 1 39 0 1
#> 113 22.86 1 34 0 0
#> 16 8.71 1 71 0 1
#> 26 15.77 1 49 0 1
#> 177 12.53 1 75 0 0
#> 127 3.53 1 62 0 1
#> 134 17.81 1 47 1 0
#> 105 19.75 1 60 0 0
#> 51 18.23 1 83 0 1
#> 157 15.10 1 47 0 0
#> 129 23.41 1 53 1 0
#> 159 10.55 1 50 0 1
#> 55 19.34 1 69 0 1
#> 97 19.14 1 65 0 1
#> 50 10.02 1 NA 1 0
#> 85 16.44 1 36 0 0
#> 51.1 18.23 1 83 0 1
#> 168 23.72 1 70 0 0
#> 158 20.14 1 74 1 0
#> 63 22.77 1 31 1 0
#> 49.1 12.19 1 48 1 0
#> 108.1 18.29 1 39 0 1
#> 195 11.76 1 NA 1 0
#> 16.1 8.71 1 71 0 1
#> 58 19.34 1 39 0 0
#> 110 17.56 1 65 0 1
#> 58.1 19.34 1 39 0 0
#> 61 10.12 1 36 0 1
#> 10 10.53 1 34 0 0
#> 192 16.44 1 31 1 0
#> 68 20.62 1 44 0 0
#> 23 16.92 1 61 0 0
#> 105.1 19.75 1 60 0 0
#> 113.1 22.86 1 34 0 0
#> 63.1 22.77 1 31 1 0
#> 5 16.43 1 51 0 1
#> 14 12.89 1 21 0 0
#> 188.1 16.16 1 46 0 1
#> 57 14.46 1 45 0 1
#> 153 21.33 1 55 1 0
#> 32 20.90 1 37 1 0
#> 113.2 22.86 1 34 0 0
#> 175 21.91 1 43 0 0
#> 90 20.94 1 50 0 1
#> 26.1 15.77 1 49 0 1
#> 194 22.40 1 38 0 1
#> 42.1 12.43 1 49 0 1
#> 14.1 12.89 1 21 0 0
#> 66 22.13 1 53 0 0
#> 92 22.92 1 47 0 1
#> 108.2 18.29 1 39 0 1
#> 66.1 22.13 1 53 0 0
#> 40 18.00 1 28 1 0
#> 171 16.57 1 41 0 1
#> 139 21.49 1 63 1 0
#> 96 14.54 1 33 0 1
#> 96.1 14.54 1 33 0 1
#> 69 23.23 1 25 0 1
#> 96.2 14.54 1 33 0 1
#> 157.1 15.10 1 47 0 0
#> 128 20.35 1 35 0 1
#> 110.1 17.56 1 65 0 1
#> 25 6.32 1 34 1 0
#> 92.1 22.92 1 47 0 1
#> 30 17.43 1 78 0 0
#> 101 9.97 1 10 0 1
#> 114 13.68 1 NA 0 0
#> 184 17.77 1 38 0 0
#> 96.3 14.54 1 33 0 1
#> 158.1 20.14 1 74 1 0
#> 52 10.42 1 52 0 1
#> 8 18.43 1 32 0 0
#> 134.1 17.81 1 47 1 0
#> 175.1 21.91 1 43 0 0
#> 70.1 7.38 1 30 1 0
#> 89 11.44 1 NA 0 0
#> 190 20.81 1 42 1 0
#> 52.1 10.42 1 52 0 1
#> 145 10.07 1 65 1 0
#> 78 23.88 1 43 0 0
#> 136.1 21.83 1 43 0 1
#> 8.1 18.43 1 32 0 0
#> 128.1 20.35 1 35 0 1
#> 99 21.19 1 38 0 1
#> 29 15.45 1 68 1 0
#> 26.2 15.77 1 49 0 1
#> 81 14.06 1 34 0 0
#> 25.1 6.32 1 34 1 0
#> 10.1 10.53 1 34 0 0
#> 23.1 16.92 1 61 0 0
#> 140 12.68 1 59 1 0
#> 29.1 15.45 1 68 1 0
#> 85.1 16.44 1 36 0 0
#> 50.1 10.02 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 81.1 14.06 1 34 0 0
#> 169 22.41 1 46 0 0
#> 167 15.55 1 56 1 0
#> 180 14.82 1 37 0 0
#> 160 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 34 24.00 0 36 0 0
#> 87 24.00 0 27 0 0
#> 172 24.00 0 41 0 0
#> 138 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 116 24.00 0 58 0 1
#> 137 24.00 0 45 1 0
#> 47 24.00 0 38 0 1
#> 135 24.00 0 58 1 0
#> 115 24.00 0 NA 1 0
#> 173 24.00 0 19 0 1
#> 109 24.00 0 48 0 0
#> 74 24.00 0 43 0 1
#> 102 24.00 0 49 0 0
#> 48 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 28 24.00 0 67 1 0
#> 33 24.00 0 53 0 0
#> 87.1 24.00 0 27 0 0
#> 84 24.00 0 39 0 1
#> 131 24.00 0 66 0 0
#> 142 24.00 0 53 0 0
#> 116.1 24.00 0 58 0 1
#> 17 24.00 0 38 0 1
#> 182 24.00 0 35 0 0
#> 19.1 24.00 0 57 0 1
#> 178 24.00 0 52 1 0
#> 7 24.00 0 37 1 0
#> 75 24.00 0 21 1 0
#> 104 24.00 0 50 1 0
#> 102.1 24.00 0 49 0 0
#> 1 24.00 0 23 1 0
#> 84.1 24.00 0 39 0 1
#> 71 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 132 24.00 0 55 0 0
#> 148 24.00 0 61 1 0
#> 104.1 24.00 0 50 1 0
#> 103 24.00 0 56 1 0
#> 135.1 24.00 0 58 1 0
#> 147 24.00 0 76 1 0
#> 53 24.00 0 32 0 1
#> 62.1 24.00 0 71 0 0
#> 103.1 24.00 0 56 1 0
#> 146 24.00 0 63 1 0
#> 120 24.00 0 68 0 1
#> 28.1 24.00 0 67 1 0
#> 12 24.00 0 63 0 0
#> 172.1 24.00 0 41 0 0
#> 7.1 24.00 0 37 1 0
#> 146.1 24.00 0 63 1 0
#> 12.1 24.00 0 63 0 0
#> 82 24.00 0 34 0 0
#> 1.1 24.00 0 23 1 0
#> 65 24.00 0 57 1 0
#> 47.1 24.00 0 38 0 1
#> 83 24.00 0 6 0 0
#> 165 24.00 0 47 0 0
#> 98 24.00 0 34 1 0
#> 115.1 24.00 0 NA 1 0
#> 138.1 24.00 0 44 1 0
#> 87.2 24.00 0 27 0 0
#> 115.2 24.00 0 NA 1 0
#> 198 24.00 0 66 0 1
#> 115.3 24.00 0 NA 1 0
#> 48.1 24.00 0 31 1 0
#> 21.1 24.00 0 47 0 0
#> 172.2 24.00 0 41 0 0
#> 54 24.00 0 53 1 0
#> 38 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 163 24.00 0 66 0 0
#> 38.1 24.00 0 31 1 0
#> 132.1 24.00 0 55 0 0
#> 28.2 24.00 0 67 1 0
#> 142.1 24.00 0 53 0 0
#> 198.1 24.00 0 66 0 1
#> 151 24.00 0 42 0 0
#> 146.2 24.00 0 63 1 0
#> 84.2 24.00 0 39 0 1
#> 67 24.00 0 25 0 0
#> 172.3 24.00 0 41 0 0
#> 9 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 186 24.00 0 45 1 0
#> 161 24.00 0 45 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.127 NA NA NA
#> 2 age, Cure model 0.00220 NA NA NA
#> 3 grade_ii, Cure model -0.216 NA NA NA
#> 4 grade_iii, Cure model 1.08 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000960 NA NA NA
#> 2 grade_ii, Survival model 0.384 NA NA NA
#> 3 grade_iii, Survival model 0.351 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.127117 0.002196 -0.216135 1.076972
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 247.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.12711651 0.00219604 -0.21613550 1.07697161
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0009598553 0.3844219906 0.3513257543
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.85715778 0.61679786 0.93701267 0.95824564 0.70550895 0.84234778
#> [7] 0.66586755 0.87183138 0.26943740 0.97224076 0.61679786 0.38448312
#> [13] 0.48744000 0.13845430 0.94414516 0.68194328 0.83484510 0.99307942
#> [19] 0.54043569 0.41324566 0.51406790 0.73666696 0.07959447 0.87916790
#> [25] 0.43210836 0.45973750 0.63329068 0.51406790 0.06035465 0.39433194
#> [31] 0.17538714 0.85715778 0.48744000 0.94414516 0.43210836 0.56620483
#> [37] 0.43210836 0.91544963 0.88647450 0.63329068 0.35489009 0.59156053
#> [43] 0.41324566 0.13845430 0.17538714 0.65768417 0.81231488 0.66586755
#> [49] 0.78973215 0.30254946 0.33445599 0.13845430 0.24644396 0.32399073
#> [55] 0.68194328 0.21144059 0.84234778 0.81231488 0.22336141 0.11238642
#> [61] 0.48744000 0.22336141 0.53164687 0.60838343 0.29152611 0.75980825
#> [67] 0.75980825 0.09661821 0.75980825 0.73666696 0.36501459 0.56620483
#> [73] 0.97923764 0.11238642 0.58307377 0.92985158 0.55757384 0.75980825
#> [79] 0.39433194 0.90101956 0.46904065 0.54043569 0.24644396 0.95824564
#> [85] 0.34475313 0.90101956 0.92266643 0.01560603 0.26943740 0.46904065
#> [91] 0.36501459 0.31335694 0.72124921 0.68194328 0.79728672 0.97923764
#> [97] 0.88647450 0.59156053 0.82733739 0.72124921 0.63329068 0.04074054
#> [103] 0.79728672 0.19919292 0.71340295 0.75206984 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 49 130 187 70 125 42 188 43 136 77 130.1 150 108
#> 12.19 16.47 9.92 7.38 15.65 12.43 16.16 12.10 21.83 7.27 16.47 20.33 18.29
#> 113 16 26 177 127 134 105 51 157 129 159 55 97
#> 22.86 8.71 15.77 12.53 3.53 17.81 19.75 18.23 15.10 23.41 10.55 19.34 19.14
#> 85 51.1 168 158 63 49.1 108.1 16.1 58 110 58.1 61 10
#> 16.44 18.23 23.72 20.14 22.77 12.19 18.29 8.71 19.34 17.56 19.34 10.12 10.53
#> 192 68 23 105.1 113.1 63.1 5 14 188.1 57 153 32 113.2
#> 16.44 20.62 16.92 19.75 22.86 22.77 16.43 12.89 16.16 14.46 21.33 20.90 22.86
#> 175 90 26.1 194 42.1 14.1 66 92 108.2 66.1 40 171 139
#> 21.91 20.94 15.77 22.40 12.43 12.89 22.13 22.92 18.29 22.13 18.00 16.57 21.49
#> 96 96.1 69 96.2 157.1 128 110.1 25 92.1 30 101 184 96.3
#> 14.54 14.54 23.23 14.54 15.10 20.35 17.56 6.32 22.92 17.43 9.97 17.77 14.54
#> 158.1 52 8 134.1 175.1 70.1 190 52.1 145 78 136.1 8.1 128.1
#> 20.14 10.42 18.43 17.81 21.91 7.38 20.81 10.42 10.07 23.88 21.83 18.43 20.35
#> 99 29 26.2 81 25.1 10.1 23.1 140 29.1 85.1 86 81.1 169
#> 21.19 15.45 15.77 14.06 6.32 10.53 16.92 12.68 15.45 16.44 23.81 14.06 22.41
#> 167 180 160 19 34 87 172 138 21 116 137 47 135
#> 15.55 14.82 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 109 74 102 48 196 28 33 87.1 84 131 142 116.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 182 19.1 178 7 75 104 102.1 1 84.1 71 62 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 104.1 103 135.1 147 53 62.1 103.1 146 120 28.1 12 172.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.1 146.1 12.1 82 1.1 65 47.1 83 165 98 138.1 87.2 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.1 21.1 172.2 54 38 119 163 38.1 132.1 28.2 142.1 198.1 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146.2 84.2 67 172.3 9 46 186 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[39]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.007538385 0.656255964 0.549076614
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.671831057 0.007540977 0.179363749
#> grade_iii, Cure model
#> 1.674752967
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 41 18.02 1 40 1 0
#> 184 17.77 1 38 0 0
#> 108 18.29 1 39 0 1
#> 26 15.77 1 49 0 1
#> 181 16.46 1 45 0 1
#> 58 19.34 1 39 0 0
#> 29 15.45 1 68 1 0
#> 51 18.23 1 83 0 1
#> 60 13.15 1 38 1 0
#> 90 20.94 1 50 0 1
#> 101 9.97 1 10 0 1
#> 140 12.68 1 59 1 0
#> 15 22.68 1 48 0 0
#> 171 16.57 1 41 0 1
#> 89 11.44 1 NA 0 0
#> 16 8.71 1 71 0 1
#> 108.1 18.29 1 39 0 1
#> 167 15.55 1 56 1 0
#> 180 14.82 1 37 0 0
#> 41.1 18.02 1 40 1 0
#> 130 16.47 1 53 0 1
#> 197 21.60 1 69 1 0
#> 41.2 18.02 1 40 1 0
#> 61 10.12 1 36 0 1
#> 127 3.53 1 62 0 1
#> 149 8.37 1 33 1 0
#> 117 17.46 1 26 0 1
#> 117.1 17.46 1 26 0 1
#> 140.1 12.68 1 59 1 0
#> 39 15.59 1 37 0 1
#> 99 21.19 1 38 0 1
#> 81 14.06 1 34 0 0
#> 24 23.89 1 38 0 0
#> 86 23.81 1 58 0 1
#> 117.2 17.46 1 26 0 1
#> 199 19.81 1 NA 0 1
#> 166 19.98 1 48 0 0
#> 59 10.16 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 63 22.77 1 31 1 0
#> 177.1 12.53 1 75 0 0
#> 76 19.22 1 54 0 1
#> 32 20.90 1 37 1 0
#> 10 10.53 1 34 0 0
#> 149.1 8.37 1 33 1 0
#> 26.1 15.77 1 49 0 1
#> 159 10.55 1 50 0 1
#> 91 5.33 1 61 0 1
#> 150 20.33 1 48 0 0
#> 63.1 22.77 1 31 1 0
#> 154 12.63 1 20 1 0
#> 16.1 8.71 1 71 0 1
#> 180.1 14.82 1 37 0 0
#> 52 10.42 1 52 0 1
#> 110 17.56 1 65 0 1
#> 197.1 21.60 1 69 1 0
#> 145 10.07 1 65 1 0
#> 93 10.33 1 52 0 1
#> 166.1 19.98 1 48 0 0
#> 78 23.88 1 43 0 0
#> 199.1 19.81 1 NA 0 1
#> 56 12.21 1 60 0 0
#> 150.1 20.33 1 48 0 0
#> 158 20.14 1 74 1 0
#> 175 21.91 1 43 0 0
#> 149.2 8.37 1 33 1 0
#> 26.2 15.77 1 49 0 1
#> 61.1 10.12 1 36 0 1
#> 13 14.34 1 54 0 1
#> 166.2 19.98 1 48 0 0
#> 167.1 15.55 1 56 1 0
#> 56.1 12.21 1 60 0 0
#> 100 16.07 1 60 0 0
#> 76.1 19.22 1 54 0 1
#> 149.3 8.37 1 33 1 0
#> 69 23.23 1 25 0 1
#> 170 19.54 1 43 0 1
#> 66 22.13 1 53 0 0
#> 108.2 18.29 1 39 0 1
#> 30 17.43 1 78 0 0
#> 113 22.86 1 34 0 0
#> 125 15.65 1 67 1 0
#> 90.1 20.94 1 50 0 1
#> 99.1 21.19 1 38 0 1
#> 93.1 10.33 1 52 0 1
#> 175.1 21.91 1 43 0 0
#> 158.1 20.14 1 74 1 0
#> 107 11.18 1 54 1 0
#> 4 17.64 1 NA 0 1
#> 8 18.43 1 32 0 0
#> 76.2 19.22 1 54 0 1
#> 69.1 23.23 1 25 0 1
#> 134 17.81 1 47 1 0
#> 158.2 20.14 1 74 1 0
#> 189 10.51 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 188 16.16 1 46 0 1
#> 36 21.19 1 48 0 1
#> 168 23.72 1 70 0 0
#> 69.2 23.23 1 25 0 1
#> 125.1 15.65 1 67 1 0
#> 171.1 16.57 1 41 0 1
#> 169 22.41 1 46 0 0
#> 16.2 8.71 1 71 0 1
#> 107.1 11.18 1 54 1 0
#> 60.1 13.15 1 38 1 0
#> 117.3 17.46 1 26 0 1
#> 15.1 22.68 1 48 0 0
#> 154.1 12.63 1 20 1 0
#> 26.3 15.77 1 49 0 1
#> 133 14.65 1 57 0 0
#> 101.1 9.97 1 10 0 1
#> 104 24.00 0 50 1 0
#> 19 24.00 0 57 0 1
#> 20 24.00 0 46 1 0
#> 182 24.00 0 35 0 0
#> 38 24.00 0 31 1 0
#> 104.1 24.00 0 50 1 0
#> 104.2 24.00 0 50 1 0
#> 185 24.00 0 44 1 0
#> 2 24.00 0 9 0 0
#> 74 24.00 0 43 0 1
#> 142 24.00 0 53 0 0
#> 54 24.00 0 53 1 0
#> 11 24.00 0 42 0 1
#> 48 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 7 24.00 0 37 1 0
#> 118 24.00 0 44 1 0
#> 178 24.00 0 52 1 0
#> 143 24.00 0 51 0 0
#> 147 24.00 0 76 1 0
#> 54.1 24.00 0 53 1 0
#> 65 24.00 0 57 1 0
#> 126 24.00 0 48 0 0
#> 116 24.00 0 58 0 1
#> 98 24.00 0 34 1 0
#> 87 24.00 0 27 0 0
#> 143.1 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 67 24.00 0 25 0 0
#> 82 24.00 0 34 0 0
#> 186 24.00 0 45 1 0
#> 82.1 24.00 0 34 0 0
#> 141 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 122.1 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 144 24.00 0 28 0 1
#> 33 24.00 0 53 0 0
#> 44 24.00 0 56 0 0
#> 46 24.00 0 71 0 0
#> 142.1 24.00 0 53 0 0
#> 103 24.00 0 56 1 0
#> 161 24.00 0 45 0 0
#> 3 24.00 0 31 1 0
#> 141.1 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 163 24.00 0 66 0 0
#> 161.1 24.00 0 45 0 0
#> 135 24.00 0 58 1 0
#> 132 24.00 0 55 0 0
#> 174 24.00 0 49 1 0
#> 33.1 24.00 0 53 0 0
#> 102 24.00 0 49 0 0
#> 84 24.00 0 39 0 1
#> 172 24.00 0 41 0 0
#> 3.1 24.00 0 31 1 0
#> 3.2 24.00 0 31 1 0
#> 174.1 24.00 0 49 1 0
#> 71 24.00 0 51 0 0
#> 87.1 24.00 0 27 0 0
#> 172.1 24.00 0 41 0 0
#> 28 24.00 0 67 1 0
#> 64 24.00 0 43 0 0
#> 72 24.00 0 40 0 1
#> 17.1 24.00 0 38 0 1
#> 21 24.00 0 47 0 0
#> 161.2 24.00 0 45 0 0
#> 186.1 24.00 0 45 1 0
#> 54.2 24.00 0 53 1 0
#> 80.1 24.00 0 41 0 0
#> 119 24.00 0 17 0 0
#> 191.1 24.00 0 60 0 1
#> 34 24.00 0 36 0 0
#> 27 24.00 0 63 1 0
#> 142.2 24.00 0 53 0 0
#> 135.1 24.00 0 58 1 0
#> 54.3 24.00 0 53 1 0
#> 95 24.00 0 68 0 1
#> 115 24.00 0 NA 1 0
#> 12 24.00 0 63 0 0
#> 121 24.00 0 57 1 0
#> 38.1 24.00 0 31 1 0
#> 119.1 24.00 0 17 0 0
#> 87.2 24.00 0 27 0 0
#> 147.1 24.00 0 76 1 0
#> 21.1 24.00 0 47 0 0
#> 27.1 24.00 0 63 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.672 NA NA NA
#> 2 age, Cure model 0.00754 NA NA NA
#> 3 grade_ii, Cure model 0.179 NA NA NA
#> 4 grade_iii, Cure model 1.67 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00754 NA NA NA
#> 2 grade_ii, Survival model 0.656 NA NA NA
#> 3 grade_iii, Survival model 0.549 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.671831 0.007541 0.179364 1.674753
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 243.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.671831057 0.007540977 0.179363749 1.674752967
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.007538385 0.656255964 0.549076614
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.66315755 0.69077278 0.63339216 0.77877816 0.75481204 0.59337653
#> [7] 0.82809692 0.65579353 0.85915537 0.48131052 0.95352689 0.86919471
#> [13] 0.33180268 0.73618622 0.96231358 0.63339216 0.81752986 0.83332321
#> [19] 0.66315755 0.74864039 0.42267692 0.66315755 0.94014084 0.99588145
#> [25] 0.97512093 0.70433775 0.70433775 0.86919471 0.81209236 0.44786351
#> [31] 0.85402678 0.05265294 0.16126102 0.70433775 0.55904433 0.88868436
#> [37] 0.29949853 0.88868436 0.60188148 0.50237047 0.92182896 0.97512093
#> [43] 0.77877816 0.91717640 0.99173264 0.51267534 0.29949853 0.87900658
#> [49] 0.96231358 0.83332321 0.92647467 0.69761549 0.42267692 0.94908782
#> [55] 0.93108427 0.55904433 0.11156867 0.89828270 0.51267534 0.53273012
#> [61] 0.39360747 0.97512093 0.77877816 0.94014084 0.84888916 0.55904433
#> [67] 0.81752986 0.89828270 0.77286270 0.60188148 0.97512093 0.22349252
#> [73] 0.58482971 0.37835503 0.63339216 0.72978480 0.27974404 0.80115973
#> [79] 0.48131052 0.44786351 0.93108427 0.39360747 0.53273012 0.90782273
#> [85] 0.62545949 0.60188148 0.22349252 0.68390752 0.53273012 0.76091231
#> [91] 0.76692124 0.44786351 0.19409573 0.22349252 0.80115973 0.73618622
#> [97] 0.36279465 0.96231358 0.90782273 0.85915537 0.70433775 0.33180268
#> [103] 0.87900658 0.77877816 0.84370126 0.95352689 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 41 184 108 26 181 58 29 51 60 90 101 140 15
#> 18.02 17.77 18.29 15.77 16.46 19.34 15.45 18.23 13.15 20.94 9.97 12.68 22.68
#> 171 16 108.1 167 180 41.1 130 197 41.2 61 127 149 117
#> 16.57 8.71 18.29 15.55 14.82 18.02 16.47 21.60 18.02 10.12 3.53 8.37 17.46
#> 117.1 140.1 39 99 81 24 86 117.2 166 177 63 177.1 76
#> 17.46 12.68 15.59 21.19 14.06 23.89 23.81 17.46 19.98 12.53 22.77 12.53 19.22
#> 32 10 149.1 26.1 159 91 150 63.1 154 16.1 180.1 52 110
#> 20.90 10.53 8.37 15.77 10.55 5.33 20.33 22.77 12.63 8.71 14.82 10.42 17.56
#> 197.1 145 93 166.1 78 56 150.1 158 175 149.2 26.2 61.1 13
#> 21.60 10.07 10.33 19.98 23.88 12.21 20.33 20.14 21.91 8.37 15.77 10.12 14.34
#> 166.2 167.1 56.1 100 76.1 149.3 69 170 66 108.2 30 113 125
#> 19.98 15.55 12.21 16.07 19.22 8.37 23.23 19.54 22.13 18.29 17.43 22.86 15.65
#> 90.1 99.1 93.1 175.1 158.1 107 8 76.2 69.1 134 158.2 79 188
#> 20.94 21.19 10.33 21.91 20.14 11.18 18.43 19.22 23.23 17.81 20.14 16.23 16.16
#> 36 168 69.2 125.1 171.1 169 16.2 107.1 60.1 117.3 15.1 154.1 26.3
#> 21.19 23.72 23.23 15.65 16.57 22.41 8.71 11.18 13.15 17.46 22.68 12.63 15.77
#> 133 101.1 104 19 20 182 38 104.1 104.2 185 2 74 142
#> 14.65 9.97 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 11 48 162 122 7 118 178 143 147 54.1 65 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 98 87 143.1 17 67 82 186 82.1 141 151 122.1 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 33 44 46 142.1 103 161 3 141.1 80 163 161.1 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 174 33.1 102 84 172 3.1 3.2 174.1 71 87.1 172.1 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 72 17.1 21 161.2 186.1 54.2 80.1 119 191.1 34 27 142.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 54.3 95 12 121 38.1 119.1 87.2 147.1 21.1 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[40]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00430987 0.82769468 0.08953657
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.01863602 0.01250226 0.46480882
#> grade_iii, Cure model
#> 1.08933309
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 189 10.51 1 NA 1 0
#> 190 20.81 1 42 1 0
#> 133 14.65 1 57 0 0
#> 107 11.18 1 54 1 0
#> 140 12.68 1 59 1 0
#> 194 22.40 1 38 0 1
#> 149 8.37 1 33 1 0
#> 136 21.83 1 43 0 1
#> 177 12.53 1 75 0 0
#> 189.1 10.51 1 NA 1 0
#> 59 10.16 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 90 20.94 1 50 0 1
#> 107.1 11.18 1 54 1 0
#> 18 15.21 1 49 1 0
#> 89 11.44 1 NA 0 0
#> 139 21.49 1 63 1 0
#> 91 5.33 1 61 0 1
#> 5 16.43 1 51 0 1
#> 97 19.14 1 65 0 1
#> 106 16.67 1 49 1 0
#> 78 23.88 1 43 0 0
#> 43 12.10 1 61 0 1
#> 164 23.60 1 76 0 1
#> 43.1 12.10 1 61 0 1
#> 125 15.65 1 67 1 0
#> 89.1 11.44 1 NA 0 0
#> 159 10.55 1 50 0 1
#> 140.1 12.68 1 59 1 0
#> 124 9.73 1 NA 1 0
#> 14 12.89 1 21 0 0
#> 5.1 16.43 1 51 0 1
#> 158 20.14 1 74 1 0
#> 90.1 20.94 1 50 0 1
#> 93 10.33 1 52 0 1
#> 66 22.13 1 53 0 0
#> 86 23.81 1 58 0 1
#> 45 17.42 1 54 0 1
#> 145 10.07 1 65 1 0
#> 76 19.22 1 54 0 1
#> 70 7.38 1 30 1 0
#> 96 14.54 1 33 0 1
#> 169 22.41 1 46 0 0
#> 183 9.24 1 67 1 0
#> 6 15.64 1 39 0 0
#> 97.1 19.14 1 65 0 1
#> 85 16.44 1 36 0 0
#> 5.2 16.43 1 51 0 1
#> 30 17.43 1 78 0 0
#> 124.1 9.73 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 159.1 10.55 1 50 0 1
#> 114.1 13.68 1 NA 0 0
#> 117 17.46 1 26 0 1
#> 70.1 7.38 1 30 1 0
#> 184 17.77 1 38 0 0
#> 13 14.34 1 54 0 1
#> 15 22.68 1 48 0 0
#> 190.1 20.81 1 42 1 0
#> 39 15.59 1 37 0 1
#> 167 15.55 1 56 1 0
#> 155 13.08 1 26 0 0
#> 125.1 15.65 1 67 1 0
#> 154 12.63 1 20 1 0
#> 6.1 15.64 1 39 0 0
#> 154.1 12.63 1 20 1 0
#> 179 18.63 1 42 0 0
#> 14.1 12.89 1 21 0 0
#> 15.1 22.68 1 48 0 0
#> 58 19.34 1 39 0 0
#> 189.2 10.51 1 NA 1 0
#> 96.1 14.54 1 33 0 1
#> 43.2 12.10 1 61 0 1
#> 107.2 11.18 1 54 1 0
#> 99 21.19 1 38 0 1
#> 16 8.71 1 71 0 1
#> 177.1 12.53 1 75 0 0
#> 188 16.16 1 46 0 1
#> 136.1 21.83 1 43 0 1
#> 117.1 17.46 1 26 0 1
#> 59.1 10.16 1 NA 1 0
#> 6.2 15.64 1 39 0 0
#> 140.2 12.68 1 59 1 0
#> 52 10.42 1 52 0 1
#> 76.1 19.22 1 54 0 1
#> 106.1 16.67 1 49 1 0
#> 128 20.35 1 35 0 1
#> 150 20.33 1 48 0 0
#> 15.2 22.68 1 48 0 0
#> 57 14.46 1 45 0 1
#> 50 10.02 1 NA 1 0
#> 117.2 17.46 1 26 0 1
#> 51 18.23 1 83 0 1
#> 181.1 16.46 1 45 0 1
#> 40 18.00 1 28 1 0
#> 128.1 20.35 1 35 0 1
#> 114.2 13.68 1 NA 0 0
#> 190.2 20.81 1 42 1 0
#> 140.3 12.68 1 59 1 0
#> 171 16.57 1 41 0 1
#> 86.1 23.81 1 58 0 1
#> 92 22.92 1 47 0 1
#> 106.2 16.67 1 49 1 0
#> 86.2 23.81 1 58 0 1
#> 194.1 22.40 1 38 0 1
#> 167.1 15.55 1 56 1 0
#> 92.1 22.92 1 47 0 1
#> 125.2 15.65 1 67 1 0
#> 43.3 12.10 1 61 0 1
#> 100 16.07 1 60 0 0
#> 52.1 10.42 1 52 0 1
#> 4 17.64 1 NA 0 1
#> 54 24.00 0 53 1 0
#> 67 24.00 0 25 0 0
#> 191 24.00 0 60 0 1
#> 35 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 186 24.00 0 45 1 0
#> 198 24.00 0 66 0 1
#> 138 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 71 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 151 24.00 0 42 0 0
#> 67.1 24.00 0 25 0 0
#> 198.1 24.00 0 66 0 1
#> 152 24.00 0 36 0 1
#> 46 24.00 0 71 0 0
#> 182 24.00 0 35 0 0
#> 200 24.00 0 64 0 0
#> 162 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 162.1 24.00 0 51 0 0
#> 72 24.00 0 40 0 1
#> 118 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 115.1 24.00 0 NA 1 0
#> 72.1 24.00 0 40 0 1
#> 132 24.00 0 55 0 0
#> 53 24.00 0 32 0 1
#> 200.1 24.00 0 64 0 0
#> 72.2 24.00 0 40 0 1
#> 19 24.00 0 57 0 1
#> 126 24.00 0 48 0 0
#> 132.1 24.00 0 55 0 0
#> 27 24.00 0 63 1 0
#> 160 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 165 24.00 0 47 0 0
#> 17 24.00 0 38 0 1
#> 104 24.00 0 50 1 0
#> 178 24.00 0 52 1 0
#> 12 24.00 0 63 0 0
#> 1.1 24.00 0 23 1 0
#> 33 24.00 0 53 0 0
#> 178.1 24.00 0 52 1 0
#> 95 24.00 0 68 0 1
#> 176 24.00 0 43 0 1
#> 98 24.00 0 34 1 0
#> 172 24.00 0 41 0 0
#> 20.1 24.00 0 46 1 0
#> 144 24.00 0 28 0 1
#> 21 24.00 0 47 0 0
#> 22 24.00 0 52 1 0
#> 122 24.00 0 66 0 0
#> 198.2 24.00 0 66 0 1
#> 120 24.00 0 68 0 1
#> 143 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 17.1 24.00 0 38 0 1
#> 160.1 24.00 0 31 1 0
#> 200.2 24.00 0 64 0 0
#> 143.1 24.00 0 51 0 0
#> 34 24.00 0 36 0 0
#> 193.1 24.00 0 45 0 1
#> 160.2 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 152.1 24.00 0 36 0 1
#> 137 24.00 0 45 1 0
#> 137.1 24.00 0 45 1 0
#> 19.1 24.00 0 57 0 1
#> 147 24.00 0 76 1 0
#> 104.1 24.00 0 50 1 0
#> 186.1 24.00 0 45 1 0
#> 53.1 24.00 0 32 0 1
#> 73 24.00 0 NA 0 1
#> 144.1 24.00 0 28 0 1
#> 71.1 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 165.1 24.00 0 47 0 0
#> 132.2 24.00 0 55 0 0
#> 131 24.00 0 66 0 0
#> 98.1 24.00 0 34 1 0
#> 87 24.00 0 27 0 0
#> 74 24.00 0 43 0 1
#> 146 24.00 0 63 1 0
#> 109 24.00 0 48 0 0
#> 98.2 24.00 0 34 1 0
#> 174 24.00 0 49 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.02 NA NA NA
#> 2 age, Cure model 0.0125 NA NA NA
#> 3 grade_ii, Cure model 0.465 NA NA NA
#> 4 grade_iii, Cure model 1.09 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00431 NA NA NA
#> 2 grade_ii, Survival model 0.828 NA NA NA
#> 3 grade_iii, Survival model 0.0895 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.0186 0.0125 0.4648 1.0893
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 252.8
#> Residual Deviance: 242.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.01863602 0.01250226 0.46480882 1.08933309
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00430987 0.82769468 0.08953657
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.231551982 0.676276527 0.865160401 0.754494977 0.121229756 0.964746031
#> [7] 0.157979849 0.809986336 0.207361749 0.865160401 0.666535624 0.182830259
#> [13] 0.991198718 0.526083474 0.337234407 0.455197256 0.005298475 0.828428666
#> [19] 0.042819314 0.828428666 0.577417040 0.892155595 0.754494977 0.734922500
#> [25] 0.526083474 0.294699797 0.207361749 0.928465834 0.145218782 0.017655156
#> [31] 0.444342320 0.937611051 0.316024790 0.973698929 0.686048090 0.108769303
#> [37] 0.946691699 0.607016942 0.337234407 0.515781465 0.526083474 0.433522659
#> [43] 0.495441026 0.892155595 0.402085425 0.973698929 0.391340382 0.715277691
#> [49] 0.076102776 0.231551982 0.636842105 0.646954031 0.725093042 0.577417040
#> [55] 0.791659272 0.607016942 0.791659272 0.358678446 0.734922500 0.076102776
#> [61] 0.305333473 0.686048090 0.828428666 0.865160401 0.195068294 0.955710567
#> [67] 0.809986336 0.556603397 0.157979849 0.402085425 0.607016942 0.754494977
#> [73] 0.910287913 0.316024790 0.455197256 0.262584359 0.283805475 0.076102776
#> [79] 0.705480279 0.402085425 0.369620716 0.495441026 0.380639740 0.262584359
#> [85] 0.231551982 0.754494977 0.485206374 0.017655156 0.054409994 0.455197256
#> [91] 0.017655156 0.121229756 0.646954031 0.054409994 0.577417040 0.828428666
#> [97] 0.566988454 0.910287913 0.000000000 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 190 133 107 140 194 149 136 177 90 107.1 18 139 91
#> 20.81 14.65 11.18 12.68 22.40 8.37 21.83 12.53 20.94 11.18 15.21 21.49 5.33
#> 5 97 106 78 43 164 43.1 125 159 140.1 14 5.1 158
#> 16.43 19.14 16.67 23.88 12.10 23.60 12.10 15.65 10.55 12.68 12.89 16.43 20.14
#> 90.1 93 66 86 45 145 76 70 96 169 183 6 97.1
#> 20.94 10.33 22.13 23.81 17.42 10.07 19.22 7.38 14.54 22.41 9.24 15.64 19.14
#> 85 5.2 30 181 159.1 117 70.1 184 13 15 190.1 39 167
#> 16.44 16.43 17.43 16.46 10.55 17.46 7.38 17.77 14.34 22.68 20.81 15.59 15.55
#> 155 125.1 154 6.1 154.1 179 14.1 15.1 58 96.1 43.2 107.2 99
#> 13.08 15.65 12.63 15.64 12.63 18.63 12.89 22.68 19.34 14.54 12.10 11.18 21.19
#> 16 177.1 188 136.1 117.1 6.2 140.2 52 76.1 106.1 128 150 15.2
#> 8.71 12.53 16.16 21.83 17.46 15.64 12.68 10.42 19.22 16.67 20.35 20.33 22.68
#> 57 117.2 51 181.1 40 128.1 190.2 140.3 171 86.1 92 106.2 86.2
#> 14.46 17.46 18.23 16.46 18.00 20.35 20.81 12.68 16.57 23.81 22.92 16.67 23.81
#> 194.1 167.1 92.1 125.2 43.3 100 52.1 54 67 191 35 1 186
#> 22.40 15.55 22.92 15.65 12.10 16.07 10.42 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 138 71 31 151 67.1 198.1 152 46 182 200 162 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.1 72 118 62 72.1 132 53 200.1 72.2 19 126 132.1 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 193 165 17 104 178 12 1.1 33 178.1 95 176 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 20.1 144 21 22 122 198.2 120 143 142 17.1 160.1 200.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143.1 34 193.1 160.2 48 9 152.1 137 137.1 19.1 147 104.1 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.1 144.1 71.1 80 165.1 132.2 131 98.1 87 74 146 109 98.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[41]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.02323952 0.17971533 0.10287801
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.952798308 0.009256976 0.669031360
#> grade_iii, Cure model
#> 1.503750304
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 154 12.63 1 20 1 0
#> 197 21.60 1 69 1 0
#> 149 8.37 1 33 1 0
#> 134 17.81 1 47 1 0
#> 184 17.77 1 38 0 0
#> 52 10.42 1 52 0 1
#> 10 10.53 1 34 0 0
#> 16 8.71 1 71 0 1
#> 40 18.00 1 28 1 0
#> 177 12.53 1 75 0 0
#> 57 14.46 1 45 0 1
#> 175 21.91 1 43 0 0
#> 101 9.97 1 10 0 1
#> 58 19.34 1 39 0 0
#> 30 17.43 1 78 0 0
#> 108 18.29 1 39 0 1
#> 192 16.44 1 31 1 0
#> 183 9.24 1 67 1 0
#> 153 21.33 1 55 1 0
#> 189 10.51 1 NA 1 0
#> 40.1 18.00 1 28 1 0
#> 4 17.64 1 NA 0 1
#> 183.1 9.24 1 67 1 0
#> 85 16.44 1 36 0 0
#> 79 16.23 1 54 1 0
#> 154.1 12.63 1 20 1 0
#> 181 16.46 1 45 0 1
#> 43 12.10 1 61 0 1
#> 57.1 14.46 1 45 0 1
#> 59 10.16 1 NA 1 0
#> 153.1 21.33 1 55 1 0
#> 149.1 8.37 1 33 1 0
#> 189.1 10.51 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 13 14.34 1 54 0 1
#> 56 12.21 1 60 0 0
#> 164.1 23.60 1 76 0 1
#> 123 13.00 1 44 1 0
#> 68 20.62 1 44 0 0
#> 128 20.35 1 35 0 1
#> 45 17.42 1 54 0 1
#> 199 19.81 1 NA 0 1
#> 23 16.92 1 61 0 0
#> 90 20.94 1 50 0 1
#> 187 9.92 1 39 1 0
#> 169 22.41 1 46 0 0
#> 97 19.14 1 65 0 1
#> 6 15.64 1 39 0 0
#> 66 22.13 1 53 0 0
#> 57.2 14.46 1 45 0 1
#> 89 11.44 1 NA 0 0
#> 136 21.83 1 43 0 1
#> 45.1 17.42 1 54 0 1
#> 106 16.67 1 49 1 0
#> 5 16.43 1 51 0 1
#> 63 22.77 1 31 1 0
#> 89.1 11.44 1 NA 0 0
#> 187.1 9.92 1 39 1 0
#> 101.1 9.97 1 10 0 1
#> 101.2 9.97 1 10 0 1
#> 183.2 9.24 1 67 1 0
#> 129 23.41 1 53 1 0
#> 190 20.81 1 42 1 0
#> 189.2 10.51 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 40.2 18.00 1 28 1 0
#> 167 15.55 1 56 1 0
#> 149.2 8.37 1 33 1 0
#> 134.1 17.81 1 47 1 0
#> 154.2 12.63 1 20 1 0
#> 164.2 23.60 1 76 0 1
#> 108.1 18.29 1 39 0 1
#> 41 18.02 1 40 1 0
#> 177.1 12.53 1 75 0 0
#> 197.1 21.60 1 69 1 0
#> 92 22.92 1 47 0 1
#> 36 21.19 1 48 0 1
#> 110 17.56 1 65 0 1
#> 13.1 14.34 1 54 0 1
#> 171 16.57 1 41 0 1
#> 61 10.12 1 36 0 1
#> 111 17.45 1 47 0 1
#> 124 9.73 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 164.3 23.60 1 76 0 1
#> 14 12.89 1 21 0 0
#> 40.3 18.00 1 28 1 0
#> 6.1 15.64 1 39 0 0
#> 37.1 12.52 1 57 1 0
#> 153.2 21.33 1 55 1 0
#> 91 5.33 1 61 0 1
#> 58.1 19.34 1 39 0 0
#> 16.1 8.71 1 71 0 1
#> 166 19.98 1 48 0 0
#> 81 14.06 1 34 0 0
#> 150 20.33 1 48 0 0
#> 159 10.55 1 50 0 1
#> 86 23.81 1 58 0 1
#> 85.1 16.44 1 36 0 0
#> 91.1 5.33 1 61 0 1
#> 45.2 17.42 1 54 0 1
#> 107 11.18 1 54 1 0
#> 199.1 19.81 1 NA 0 1
#> 13.2 14.34 1 54 0 1
#> 181.1 16.46 1 45 0 1
#> 195 11.76 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 110.1 17.56 1 65 0 1
#> 70 7.38 1 30 1 0
#> 177.2 12.53 1 75 0 0
#> 181.2 16.46 1 45 0 1
#> 168 23.72 1 70 0 0
#> 21 24.00 0 47 0 0
#> 7 24.00 0 37 1 0
#> 34 24.00 0 36 0 0
#> 147 24.00 0 76 1 0
#> 151 24.00 0 42 0 0
#> 162 24.00 0 51 0 0
#> 174 24.00 0 49 1 0
#> 178 24.00 0 52 1 0
#> 186 24.00 0 45 1 0
#> 9 24.00 0 31 1 0
#> 178.1 24.00 0 52 1 0
#> 172 24.00 0 41 0 0
#> 152 24.00 0 36 0 1
#> 200 24.00 0 64 0 0
#> 165 24.00 0 47 0 0
#> 74 24.00 0 43 0 1
#> 17 24.00 0 38 0 1
#> 9.1 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 121 24.00 0 57 1 0
#> 172.1 24.00 0 41 0 0
#> 53 24.00 0 32 0 1
#> 185 24.00 0 44 1 0
#> 152.1 24.00 0 36 0 1
#> 104 24.00 0 50 1 0
#> 35 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 162.1 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#> 83 24.00 0 6 0 0
#> 87 24.00 0 27 0 0
#> 54 24.00 0 53 1 0
#> 196 24.00 0 19 0 0
#> 186.1 24.00 0 45 1 0
#> 74.1 24.00 0 43 0 1
#> 109 24.00 0 48 0 0
#> 121.1 24.00 0 57 1 0
#> 33 24.00 0 53 0 0
#> 35.1 24.00 0 51 0 0
#> 196.1 24.00 0 19 0 0
#> 119.1 24.00 0 17 0 0
#> 94 24.00 0 51 0 1
#> 27 24.00 0 63 1 0
#> 11 24.00 0 42 0 1
#> 34.1 24.00 0 36 0 0
#> 87.1 24.00 0 27 0 0
#> 161 24.00 0 45 0 0
#> 28 24.00 0 67 1 0
#> 162.2 24.00 0 51 0 0
#> 185.1 24.00 0 44 1 0
#> 109.1 24.00 0 48 0 0
#> 44 24.00 0 56 0 0
#> 2.1 24.00 0 9 0 0
#> 28.1 24.00 0 67 1 0
#> 191 24.00 0 60 0 1
#> 182 24.00 0 35 0 0
#> 109.2 24.00 0 48 0 0
#> 83.1 24.00 0 6 0 0
#> 146 24.00 0 63 1 0
#> 31 24.00 0 36 0 1
#> 142 24.00 0 53 0 0
#> 115 24.00 0 NA 1 0
#> 191.1 24.00 0 60 0 1
#> 163 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 162.3 24.00 0 51 0 0
#> 28.2 24.00 0 67 1 0
#> 83.2 24.00 0 6 0 0
#> 147.1 24.00 0 76 1 0
#> 165.1 24.00 0 47 0 0
#> 75 24.00 0 21 1 0
#> 20 24.00 0 46 1 0
#> 21.1 24.00 0 47 0 0
#> 33.1 24.00 0 53 0 0
#> 94.1 24.00 0 51 0 1
#> 54.1 24.00 0 53 1 0
#> 98 24.00 0 34 1 0
#> 64 24.00 0 43 0 0
#> 73 24.00 0 NA 0 1
#> 48 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 138 24.00 0 44 1 0
#> 94.2 24.00 0 51 0 1
#> 193 24.00 0 45 0 1
#> 35.2 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 146.1 24.00 0 63 1 0
#> 48.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.953 NA NA NA
#> 2 age, Cure model 0.00926 NA NA NA
#> 3 grade_ii, Cure model 0.669 NA NA NA
#> 4 grade_iii, Cure model 1.50 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0232 NA NA NA
#> 2 grade_ii, Survival model 0.180 NA NA NA
#> 3 grade_iii, Survival model 0.103 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.952798 0.009257 0.669031 1.503750
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 239.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.952798308 0.009256976 0.669031360 1.503750304
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.02323952 0.17971533 0.10287801
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 3.877608e-01 3.298284e-03 8.560966e-01 6.320496e-02 7.304086e-02
#> [6] 6.058948e-01 5.865899e-01 8.104236e-01 4.649180e-02 4.315103e-01
#> [11] 2.554896e-01 1.932755e-03 6.456745e-01 2.482482e-02 9.589198e-02
#> [16] 3.465267e-02 1.732192e-01 7.457175e-01 5.175690e-03 4.649180e-02
#> [21] 7.457175e-01 1.732192e-01 2.116394e-01 3.877608e-01 1.472049e-01
#> [26] 5.309121e-01 2.554896e-01 5.175690e-03 8.560966e-01 8.642699e-06
#> [31] 2.913078e-01 5.132004e-01 8.642699e-06 3.585064e-01 1.461485e-02
#> [36] 1.687315e-02 1.023838e-01 1.231936e-01 1.067490e-02 7.046379e-01
#> [41] 9.984789e-04 3.106854e-02 2.221855e-01 1.411406e-03 2.554896e-01
#> [46] 2.561775e-03 1.023838e-01 1.309120e-01 2.014285e-01 6.741467e-04
#> [51] 7.046379e-01 6.456745e-01 6.456745e-01 7.457175e-01 2.161445e-04
#> [56] 1.256007e-02 4.792539e-01 4.649180e-02 2.439818e-01 8.560966e-01
#> [61] 6.320496e-02 3.877608e-01 8.642699e-06 3.465267e-02 4.227874e-02
#> [66] 4.315103e-01 3.298284e-03 4.051168e-04 8.984920e-03 7.835403e-02
#> [71] 2.913078e-01 1.389217e-01 6.256203e-01 8.974822e-02 3.443172e-01
#> [76] 8.642699e-06 3.730228e-01 4.649180e-02 2.221855e-01 4.792539e-01
#> [81] 5.175690e-03 9.503577e-01 2.482482e-02 8.104236e-01 2.194385e-02
#> [86] 3.304173e-01 1.929667e-02 5.676258e-01 3.403906e-08 1.732192e-01
#> [91] 9.503577e-01 1.023838e-01 5.490668e-01 2.913078e-01 1.472049e-01
#> [96] 7.835403e-02 9.261416e-01 4.315103e-01 1.472049e-01 1.097172e-06
#> [101] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00
#>
#> $Time
#> 154 197 149 134 184 52 10 16 40 177 57 175 101
#> 12.63 21.60 8.37 17.81 17.77 10.42 10.53 8.71 18.00 12.53 14.46 21.91 9.97
#> 58 30 108 192 183 153 40.1 183.1 85 79 154.1 181 43
#> 19.34 17.43 18.29 16.44 9.24 21.33 18.00 9.24 16.44 16.23 12.63 16.46 12.10
#> 57.1 153.1 149.1 164 13 56 164.1 123 68 128 45 23 90
#> 14.46 21.33 8.37 23.60 14.34 12.21 23.60 13.00 20.62 20.35 17.42 16.92 20.94
#> 187 169 97 6 66 57.2 136 45.1 106 5 63 187.1 101.1
#> 9.92 22.41 19.14 15.64 22.13 14.46 21.83 17.42 16.67 16.43 22.77 9.92 9.97
#> 101.2 183.2 129 190 37 40.2 167 149.2 134.1 154.2 164.2 108.1 41
#> 9.97 9.24 23.41 20.81 12.52 18.00 15.55 8.37 17.81 12.63 23.60 18.29 18.02
#> 177.1 197.1 92 36 110 13.1 171 61 111 60 164.3 14 40.3
#> 12.53 21.60 22.92 21.19 17.56 14.34 16.57 10.12 17.45 13.15 23.60 12.89 18.00
#> 6.1 37.1 153.2 91 58.1 16.1 166 81 150 159 86 85.1 91.1
#> 15.64 12.52 21.33 5.33 19.34 8.71 19.98 14.06 20.33 10.55 23.81 16.44 5.33
#> 45.2 107 13.2 181.1 110.1 70 177.2 181.2 168 21 7 34 147
#> 17.42 11.18 14.34 16.46 17.56 7.38 12.53 16.46 23.72 24.00 24.00 24.00 24.00
#> 151 162 174 178 186 9 178.1 172 152 200 165 74 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 119 121 172.1 53 185 152.1 104 35 2 162.1 102 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 54 196 186.1 74.1 109 121.1 33 35.1 196.1 119.1 94 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 34.1 87.1 161 28 162.2 185.1 109.1 44 2.1 28.1 191 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109.2 83.1 146 31 142 191.1 163 22 162.3 28.2 83.2 147.1 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 20 21.1 33.1 94.1 54.1 98 64 48 95 138 94.2 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.2 65 146.1 48.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[42]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004179013 0.341716687 0.271705215
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.56400720 0.01128498 -0.46945250
#> grade_iii, Cure model
#> 1.06606383
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 86 23.81 1 58 0 1
#> 159 10.55 1 50 0 1
#> 16 8.71 1 71 0 1
#> 66 22.13 1 53 0 0
#> 110 17.56 1 65 0 1
#> 125 15.65 1 67 1 0
#> 97 19.14 1 65 0 1
#> 88 18.37 1 47 0 0
#> 110.1 17.56 1 65 0 1
#> 114 13.68 1 NA 0 0
#> 58 19.34 1 39 0 0
#> 155 13.08 1 26 0 0
#> 110.2 17.56 1 65 0 1
#> 175 21.91 1 43 0 0
#> 26 15.77 1 49 0 1
#> 49 12.19 1 48 1 0
#> 179 18.63 1 42 0 0
#> 180 14.82 1 37 0 0
#> 128 20.35 1 35 0 1
#> 130 16.47 1 53 0 1
#> 59 10.16 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 4 17.64 1 NA 0 1
#> 130.1 16.47 1 53 0 1
#> 101 9.97 1 10 0 1
#> 184 17.77 1 38 0 0
#> 50 10.02 1 NA 1 0
#> 197 21.60 1 69 1 0
#> 30 17.43 1 78 0 0
#> 157 15.10 1 47 0 0
#> 108 18.29 1 39 0 1
#> 77 7.27 1 67 0 1
#> 155.1 13.08 1 26 0 0
#> 13 14.34 1 54 0 1
#> 195 11.76 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 113 22.86 1 34 0 0
#> 113.1 22.86 1 34 0 0
#> 93 10.33 1 52 0 1
#> 100 16.07 1 60 0 0
#> 154 12.63 1 20 1 0
#> 86.1 23.81 1 58 0 1
#> 177 12.53 1 75 0 0
#> 79 16.23 1 54 1 0
#> 170 19.54 1 43 0 1
#> 179.1 18.63 1 42 0 0
#> 30.1 17.43 1 78 0 0
#> 61 10.12 1 36 0 1
#> 177.1 12.53 1 75 0 0
#> 32 20.90 1 37 1 0
#> 107 11.18 1 54 1 0
#> 93.1 10.33 1 52 0 1
#> 171 16.57 1 41 0 1
#> 99 21.19 1 38 0 1
#> 181 16.46 1 45 0 1
#> 68 20.62 1 44 0 0
#> 188 16.16 1 46 0 1
#> 50.1 10.02 1 NA 1 0
#> 170.1 19.54 1 43 0 1
#> 25 6.32 1 34 1 0
#> 41 18.02 1 40 1 0
#> 52.1 10.42 1 52 0 1
#> 110.3 17.56 1 65 0 1
#> 78 23.88 1 43 0 0
#> 76 19.22 1 54 0 1
#> 189 10.51 1 NA 1 0
#> 154.1 12.63 1 20 1 0
#> 101.1 9.97 1 10 0 1
#> 32.1 20.90 1 37 1 0
#> 24 23.89 1 38 0 0
#> 10 10.53 1 34 0 0
#> 60 13.15 1 38 1 0
#> 166 19.98 1 48 0 0
#> 32.2 20.90 1 37 1 0
#> 58.1 19.34 1 39 0 0
#> 164 23.60 1 76 0 1
#> 69 23.23 1 25 0 1
#> 184.1 17.77 1 38 0 0
#> 97.1 19.14 1 65 0 1
#> 88.1 18.37 1 47 0 0
#> 4.1 17.64 1 NA 0 1
#> 13.1 14.34 1 54 0 1
#> 184.2 17.77 1 38 0 0
#> 29 15.45 1 68 1 0
#> 36 21.19 1 48 0 1
#> 66.1 22.13 1 53 0 0
#> 106 16.67 1 49 1 0
#> 51 18.23 1 83 0 1
#> 123 13.00 1 44 1 0
#> 16.1 8.71 1 71 0 1
#> 14 12.89 1 21 0 0
#> 70 7.38 1 30 1 0
#> 5 16.43 1 51 0 1
#> 88.2 18.37 1 47 0 0
#> 63 22.77 1 31 1 0
#> 108.1 18.29 1 39 0 1
#> 30.2 17.43 1 78 0 0
#> 4.2 17.64 1 NA 0 1
#> 164.1 23.60 1 76 0 1
#> 50.2 10.02 1 NA 1 0
#> 108.2 18.29 1 39 0 1
#> 158 20.14 1 74 1 0
#> 179.2 18.63 1 42 0 0
#> 26.1 15.77 1 49 0 1
#> 197.1 21.60 1 69 1 0
#> 97.2 19.14 1 65 0 1
#> 97.3 19.14 1 65 0 1
#> 56 12.21 1 60 0 0
#> 128.1 20.35 1 35 0 1
#> 37 12.52 1 57 1 0
#> 197.2 21.60 1 69 1 0
#> 85 16.44 1 36 0 0
#> 20 24.00 0 46 1 0
#> 75 24.00 0 21 1 0
#> 147 24.00 0 76 1 0
#> 11 24.00 0 42 0 1
#> 151 24.00 0 42 0 0
#> 46 24.00 0 71 0 0
#> 162 24.00 0 51 0 0
#> 193 24.00 0 45 0 1
#> 193.1 24.00 0 45 0 1
#> 2 24.00 0 9 0 0
#> 122 24.00 0 66 0 0
#> 156 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 33 24.00 0 53 0 0
#> 75.1 24.00 0 21 1 0
#> 137 24.00 0 45 1 0
#> 137.1 24.00 0 45 1 0
#> 156.1 24.00 0 50 1 0
#> 118 24.00 0 44 1 0
#> 2.1 24.00 0 9 0 0
#> 109 24.00 0 48 0 0
#> 152 24.00 0 36 0 1
#> 120 24.00 0 68 0 1
#> 174 24.00 0 49 1 0
#> 31 24.00 0 36 0 1
#> 1 24.00 0 23 1 0
#> 54 24.00 0 53 1 0
#> 9 24.00 0 31 1 0
#> 151.1 24.00 0 42 0 0
#> 102 24.00 0 49 0 0
#> 196 24.00 0 19 0 0
#> 173 24.00 0 19 0 1
#> 28 24.00 0 67 1 0
#> 62 24.00 0 71 0 0
#> 1.1 24.00 0 23 1 0
#> 112 24.00 0 61 0 0
#> 185 24.00 0 44 1 0
#> 94 24.00 0 51 0 1
#> 102.1 24.00 0 49 0 0
#> 135 24.00 0 58 1 0
#> 46.1 24.00 0 71 0 0
#> 116 24.00 0 58 0 1
#> 28.1 24.00 0 67 1 0
#> 98 24.00 0 34 1 0
#> 156.2 24.00 0 50 1 0
#> 83 24.00 0 6 0 0
#> 11.1 24.00 0 42 0 1
#> 62.1 24.00 0 71 0 0
#> 80 24.00 0 41 0 0
#> 118.1 24.00 0 44 1 0
#> 135.1 24.00 0 58 1 0
#> 118.2 24.00 0 44 1 0
#> 151.2 24.00 0 42 0 0
#> 98.1 24.00 0 34 1 0
#> 193.2 24.00 0 45 0 1
#> 46.2 24.00 0 71 0 0
#> 27 24.00 0 63 1 0
#> 1.2 24.00 0 23 1 0
#> 71 24.00 0 51 0 0
#> 33.1 24.00 0 53 0 0
#> 172 24.00 0 41 0 0
#> 165 24.00 0 47 0 0
#> 172.1 24.00 0 41 0 0
#> 118.3 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 20.1 24.00 0 46 1 0
#> 193.3 24.00 0 45 0 1
#> 53 24.00 0 32 0 1
#> 112.1 24.00 0 61 0 0
#> 7 24.00 0 37 1 0
#> 143.1 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 156.3 24.00 0 50 1 0
#> 67 24.00 0 25 0 0
#> 131 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 28.2 24.00 0 67 1 0
#> 126 24.00 0 48 0 0
#> 9.1 24.00 0 31 1 0
#> 173.1 24.00 0 19 0 1
#> 160 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 95 24.00 0 68 0 1
#> 75.2 24.00 0 21 1 0
#> 163 24.00 0 66 0 0
#> 163.1 24.00 0 66 0 0
#> 12 24.00 0 63 0 0
#> 174.1 24.00 0 49 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.564 NA NA NA
#> 2 age, Cure model 0.0113 NA NA NA
#> 3 grade_ii, Cure model -0.469 NA NA NA
#> 4 grade_iii, Cure model 1.07 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00418 NA NA NA
#> 2 grade_ii, Survival model 0.342 NA NA NA
#> 3 grade_iii, Survival model 0.272 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.56401 0.01128 -0.46945 1.06606
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262.4
#> Residual Deviance: 243 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.56400720 0.01128498 -0.46945250 1.06606383
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004179013 0.341716687 0.271705215
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.026559533 0.853286202 0.941528958 0.104350425 0.479549286 0.665924150
#> [7] 0.307509733 0.373208677 0.479549286 0.278620507 0.735100645 0.479549286
#> [13] 0.124333676 0.646273369 0.833534125 0.344611726 0.695601308 0.221292984
#> [19] 0.567127604 0.873024226 0.567127604 0.922069099 0.450564735 0.134909032
#> [25] 0.517802096 0.685694803 0.402202717 0.970759484 0.735100645 0.705528069
#> [31] 0.990261112 0.074635643 0.074635643 0.892640813 0.636351110 0.774578089
#> [37] 0.026559533 0.794103301 0.616562061 0.259653885 0.344611726 0.517802096
#> [43] 0.912233349 0.794103301 0.183608888 0.843417278 0.892640813 0.557184799
#> [49] 0.163894317 0.586803753 0.211484258 0.626463047 0.259653885 0.980521010
#> [55] 0.440782978 0.873024226 0.479549286 0.014690675 0.297783751 0.774578089
#> [61] 0.922069099 0.183608888 0.004549906 0.863147741 0.725216039 0.249921284
#> [67] 0.183608888 0.278620507 0.045285100 0.064484836 0.450564735 0.307509733
#> [73] 0.373208677 0.705528069 0.450564735 0.675813757 0.163894317 0.104350425
#> [79] 0.547223231 0.430959656 0.754791124 0.941528958 0.764679229 0.960998768
#> [85] 0.606641476 0.373208677 0.094239382 0.402202717 0.517802096 0.045285100
#> [91] 0.402202717 0.240257124 0.344611726 0.646273369 0.134909032 0.307509733
#> [97] 0.307509733 0.823633180 0.221292984 0.813758562 0.134909032 0.596711098
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 86 159 16 66 110 125 97 88 110.1 58 155 110.2 175
#> 23.81 10.55 8.71 22.13 17.56 15.65 19.14 18.37 17.56 19.34 13.08 17.56 21.91
#> 26 49 179 180 128 130 52 130.1 101 184 197 30 157
#> 15.77 12.19 18.63 14.82 20.35 16.47 10.42 16.47 9.97 17.77 21.60 17.43 15.10
#> 108 77 155.1 13 127 113 113.1 93 100 154 86.1 177 79
#> 18.29 7.27 13.08 14.34 3.53 22.86 22.86 10.33 16.07 12.63 23.81 12.53 16.23
#> 170 179.1 30.1 61 177.1 32 107 93.1 171 99 181 68 188
#> 19.54 18.63 17.43 10.12 12.53 20.90 11.18 10.33 16.57 21.19 16.46 20.62 16.16
#> 170.1 25 41 52.1 110.3 78 76 154.1 101.1 32.1 24 10 60
#> 19.54 6.32 18.02 10.42 17.56 23.88 19.22 12.63 9.97 20.90 23.89 10.53 13.15
#> 166 32.2 58.1 164 69 184.1 97.1 88.1 13.1 184.2 29 36 66.1
#> 19.98 20.90 19.34 23.60 23.23 17.77 19.14 18.37 14.34 17.77 15.45 21.19 22.13
#> 106 51 123 16.1 14 70 5 88.2 63 108.1 30.2 164.1 108.2
#> 16.67 18.23 13.00 8.71 12.89 7.38 16.43 18.37 22.77 18.29 17.43 23.60 18.29
#> 158 179.2 26.1 197.1 97.2 97.3 56 128.1 37 197.2 85 20 75
#> 20.14 18.63 15.77 21.60 19.14 19.14 12.21 20.35 12.52 21.60 16.44 24.00 24.00
#> 147 11 151 46 162 193 193.1 2 122 156 143 33 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 137.1 156.1 118 2.1 109 152 120 174 31 1 54 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 102 196 173 28 62 1.1 112 185 94 102.1 135 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 28.1 98 156.2 83 11.1 62.1 80 118.1 135.1 118.2 151.2 98.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.2 46.2 27 1.2 71 33.1 172 165 172.1 118.3 104 20.1 193.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 112.1 7 143.1 119 156.3 67 131 48 28.2 126 9.1 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 74 95 75.2 163 163.1 12 174.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[43]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004852412 0.656855908 0.426986130
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.517873444 0.006195792 0.077843914
#> grade_iii, Cure model
#> 1.328734911
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 168 23.72 1 70 0 0
#> 37 12.52 1 57 1 0
#> 76 19.22 1 54 0 1
#> 42 12.43 1 49 0 1
#> 68 20.62 1 44 0 0
#> 69 23.23 1 25 0 1
#> 90 20.94 1 50 0 1
#> 134 17.81 1 47 1 0
#> 59 10.16 1 NA 1 0
#> 70 7.38 1 30 1 0
#> 199 19.81 1 NA 0 1
#> 40 18.00 1 28 1 0
#> 150 20.33 1 48 0 0
#> 93 10.33 1 52 0 1
#> 108 18.29 1 39 0 1
#> 99 21.19 1 38 0 1
#> 111 17.45 1 47 0 1
#> 6 15.64 1 39 0 0
#> 40.1 18.00 1 28 1 0
#> 101 9.97 1 10 0 1
#> 66 22.13 1 53 0 0
#> 70.1 7.38 1 30 1 0
#> 155 13.08 1 26 0 0
#> 167 15.55 1 56 1 0
#> 113 22.86 1 34 0 0
#> 99.1 21.19 1 38 0 1
#> 58 19.34 1 39 0 0
#> 85 16.44 1 36 0 0
#> 6.1 15.64 1 39 0 0
#> 69.1 23.23 1 25 0 1
#> 32 20.90 1 37 1 0
#> 41 18.02 1 40 1 0
#> 58.1 19.34 1 39 0 0
#> 111.1 17.45 1 47 0 1
#> 155.1 13.08 1 26 0 0
#> 39 15.59 1 37 0 1
#> 10 10.53 1 34 0 0
#> 70.2 7.38 1 30 1 0
#> 29 15.45 1 68 1 0
#> 76.1 19.22 1 54 0 1
#> 30 17.43 1 78 0 0
#> 184 17.77 1 38 0 0
#> 78 23.88 1 43 0 0
#> 45 17.42 1 54 0 1
#> 13 14.34 1 54 0 1
#> 180 14.82 1 37 0 0
#> 36 21.19 1 48 0 1
#> 59.1 10.16 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 158 20.14 1 74 1 0
#> 195 11.76 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 125 15.65 1 67 1 0
#> 164 23.60 1 76 0 1
#> 127 3.53 1 62 0 1
#> 56 12.21 1 60 0 0
#> 37.1 12.52 1 57 1 0
#> 150.1 20.33 1 48 0 0
#> 105 19.75 1 60 0 0
#> 99.2 21.19 1 38 0 1
#> 39.1 15.59 1 37 0 1
#> 50 10.02 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 41.1 18.02 1 40 1 0
#> 181 16.46 1 45 0 1
#> 124 9.73 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 130 16.47 1 53 0 1
#> 24 23.89 1 38 0 0
#> 124.1 9.73 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 136 21.83 1 43 0 1
#> 149.1 8.37 1 33 1 0
#> 183 9.24 1 67 1 0
#> 91.1 5.33 1 61 0 1
#> 52 10.42 1 52 0 1
#> 106.1 16.67 1 49 1 0
#> 93.1 10.33 1 52 0 1
#> 24.1 23.89 1 38 0 0
#> 107 11.18 1 54 1 0
#> 189 10.51 1 NA 1 0
#> 105.1 19.75 1 60 0 0
#> 190 20.81 1 42 1 0
#> 170 19.54 1 43 0 1
#> 101.1 9.97 1 10 0 1
#> 51 18.23 1 83 0 1
#> 130.1 16.47 1 53 0 1
#> 155.2 13.08 1 26 0 0
#> 41.2 18.02 1 40 1 0
#> 79 16.23 1 54 1 0
#> 23 16.92 1 61 0 0
#> 157 15.10 1 47 0 0
#> 159 10.55 1 50 0 1
#> 10.1 10.53 1 34 0 0
#> 57 14.46 1 45 0 1
#> 89 11.44 1 NA 0 0
#> 180.1 14.82 1 37 0 0
#> 55 19.34 1 69 0 1
#> 171 16.57 1 41 0 1
#> 127.1 3.53 1 62 0 1
#> 90.1 20.94 1 50 0 1
#> 159.1 10.55 1 50 0 1
#> 154 12.63 1 20 1 0
#> 51.1 18.23 1 83 0 1
#> 42.1 12.43 1 49 0 1
#> 13.1 14.34 1 54 0 1
#> 14 12.89 1 21 0 0
#> 13.2 14.34 1 54 0 1
#> 60 13.15 1 38 1 0
#> 153 21.33 1 55 1 0
#> 52.1 10.42 1 52 0 1
#> 184.1 17.77 1 38 0 0
#> 151 24.00 0 42 0 0
#> 64 24.00 0 43 0 0
#> 33 24.00 0 53 0 0
#> 65 24.00 0 57 1 0
#> 198 24.00 0 66 0 1
#> 35 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 103 24.00 0 56 1 0
#> 38 24.00 0 31 1 0
#> 64.1 24.00 0 43 0 0
#> 173 24.00 0 19 0 1
#> 172 24.00 0 41 0 0
#> 141 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 74 24.00 0 43 0 1
#> 142 24.00 0 53 0 0
#> 172.1 24.00 0 41 0 0
#> 35.1 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 83 24.00 0 6 0 0
#> 82 24.00 0 34 0 0
#> 104 24.00 0 50 1 0
#> 151.1 24.00 0 42 0 0
#> 33.1 24.00 0 53 0 0
#> 121 24.00 0 57 1 0
#> 73 24.00 0 NA 0 1
#> 83.1 24.00 0 6 0 0
#> 142.1 24.00 0 53 0 0
#> 161 24.00 0 45 0 0
#> 94 24.00 0 51 0 1
#> 98 24.00 0 34 1 0
#> 84 24.00 0 39 0 1
#> 104.1 24.00 0 50 1 0
#> 17 24.00 0 38 0 1
#> 46 24.00 0 71 0 0
#> 138 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 75 24.00 0 21 1 0
#> 87 24.00 0 27 0 0
#> 144 24.00 0 28 0 1
#> 12 24.00 0 63 0 0
#> 118 24.00 0 44 1 0
#> 94.1 24.00 0 51 0 1
#> 35.2 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 72 24.00 0 40 0 1
#> 137.1 24.00 0 45 1 0
#> 182 24.00 0 35 0 0
#> 163 24.00 0 66 0 0
#> 135.1 24.00 0 58 1 0
#> 1 24.00 0 23 1 0
#> 48 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 7 24.00 0 37 1 0
#> 152 24.00 0 36 0 1
#> 162 24.00 0 51 0 0
#> 162.1 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 54.1 24.00 0 53 1 0
#> 44 24.00 0 56 0 0
#> 162.2 24.00 0 51 0 0
#> 120 24.00 0 68 0 1
#> 118.1 24.00 0 44 1 0
#> 72.1 24.00 0 40 0 1
#> 82.1 24.00 0 34 0 0
#> 143 24.00 0 51 0 0
#> 112 24.00 0 61 0 0
#> 151.2 24.00 0 42 0 0
#> 112.1 24.00 0 61 0 0
#> 141.1 24.00 0 44 1 0
#> 118.2 24.00 0 44 1 0
#> 135.2 24.00 0 58 1 0
#> 82.2 24.00 0 34 0 0
#> 174 24.00 0 49 1 0
#> 53 24.00 0 32 0 1
#> 200 24.00 0 64 0 0
#> 115 24.00 0 NA 1 0
#> 75.1 24.00 0 21 1 0
#> 7.1 24.00 0 37 1 0
#> 141.2 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 131 24.00 0 66 0 0
#> 75.2 24.00 0 21 1 0
#> 53.1 24.00 0 32 0 1
#> 12.1 24.00 0 63 0 0
#> 47 24.00 0 38 0 1
#> 1.1 24.00 0 23 1 0
#> 46.1 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.518 NA NA NA
#> 2 age, Cure model 0.00620 NA NA NA
#> 3 grade_ii, Cure model 0.0778 NA NA NA
#> 4 grade_iii, Cure model 1.33 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00485 NA NA NA
#> 2 grade_ii, Survival model 0.657 NA NA NA
#> 3 grade_iii, Survival model 0.427 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.517873 0.006196 0.077844 1.328735
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 244.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.517873444 0.006195792 0.077843914 1.328734911
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004852412 0.656855908 0.426986130
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.041963331 0.772691964 0.347855041 0.789978987 0.244749161 0.072678826
#> [7] 0.202821536 0.446643871 0.943204346 0.427797319 0.255092058 0.875823487
#> [13] 0.368347170 0.161925030 0.474830652 0.604119571 0.427797319 0.901373386
#> [19] 0.110098027 0.943204346 0.728807212 0.640086706 0.096865875 0.161925030
#> [25] 0.317256361 0.576792443 0.604119571 0.072678826 0.223966425 0.398983471
#> [31] 0.317256361 0.474830652 0.728807212 0.622176081 0.841588492 0.943204346
#> [37] 0.649046252 0.347855041 0.493438342 0.456061195 0.028014965 0.502888282
#> [43] 0.693673943 0.666894903 0.161925030 0.967534653 0.275699363 0.926626979
#> [49] 0.595069836 0.057430784 0.983785327 0.807187587 0.772691964 0.255092058
#> [55] 0.286066171 0.161925030 0.622176081 0.521769269 0.398983471 0.567642575
#> [61] 0.892845077 0.549422756 0.008416989 0.136953246 0.123702530 0.926626979
#> [67] 0.918203509 0.967534653 0.858738541 0.521769269 0.875823487 0.008416989
#> [73] 0.815861724 0.286066171 0.234489668 0.306797233 0.901373386 0.378661766
#> [79] 0.549422756 0.728807212 0.398983471 0.585965637 0.512306488 0.657958234
#> [85] 0.824491443 0.841588492 0.684726522 0.666894903 0.317256361 0.540178859
#> [91] 0.983785327 0.202821536 0.824491443 0.763908131 0.378661766 0.789978987
#> [97] 0.693673943 0.755047855 0.693673943 0.719991320 0.149686958 0.858738541
#> [103] 0.456061195 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 168 37 76 42 68 69 90 134 70 40 150 93 108
#> 23.72 12.52 19.22 12.43 20.62 23.23 20.94 17.81 7.38 18.00 20.33 10.33 18.29
#> 99 111 6 40.1 101 66 70.1 155 167 113 99.1 58 85
#> 21.19 17.45 15.64 18.00 9.97 22.13 7.38 13.08 15.55 22.86 21.19 19.34 16.44
#> 6.1 69.1 32 41 58.1 111.1 155.1 39 10 70.2 29 76.1 30
#> 15.64 23.23 20.90 18.02 19.34 17.45 13.08 15.59 10.53 7.38 15.45 19.22 17.43
#> 184 78 45 13 180 36 91 158 149 125 164 127 56
#> 17.77 23.88 17.42 14.34 14.82 21.19 5.33 20.14 8.37 15.65 23.60 3.53 12.21
#> 37.1 150.1 105 99.2 39.1 106 41.1 181 61 130 24 139 136
#> 12.52 20.33 19.75 21.19 15.59 16.67 18.02 16.46 10.12 16.47 23.89 21.49 21.83
#> 149.1 183 91.1 52 106.1 93.1 24.1 107 105.1 190 170 101.1 51
#> 8.37 9.24 5.33 10.42 16.67 10.33 23.89 11.18 19.75 20.81 19.54 9.97 18.23
#> 130.1 155.2 41.2 79 23 157 159 10.1 57 180.1 55 171 127.1
#> 16.47 13.08 18.02 16.23 16.92 15.10 10.55 10.53 14.46 14.82 19.34 16.57 3.53
#> 90.1 159.1 154 51.1 42.1 13.1 14 13.2 60 153 52.1 184.1 151
#> 20.94 10.55 12.63 18.23 12.43 14.34 12.89 14.34 13.15 21.33 10.42 17.77 24.00
#> 64 33 65 198 35 137 103 38 64.1 173 172 141 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 142 172.1 35.1 109 83 82 104 151.1 33.1 121 83.1 142.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 94 98 84 104.1 17 46 138 196 75 87 144 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 94.1 35.2 178 72 137.1 182 163 135.1 1 48 54 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 162 162.1 22 54.1 44 162.2 120 118.1 72.1 82.1 143 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.2 112.1 141.1 118.2 135.2 82.2 174 53 200 75.1 7.1 141.2 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 75.2 53.1 12.1 47 1.1 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[44]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01271082 0.25884702 0.35170598
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.93041199 0.02583984 -0.30926814
#> grade_iii, Cure model
#> -0.12588558
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 66 22.13 1 53 0 0
#> 199 19.81 1 NA 0 1
#> 89 11.44 1 NA 0 0
#> 117 17.46 1 26 0 1
#> 8 18.43 1 32 0 0
#> 58 19.34 1 39 0 0
#> 179 18.63 1 42 0 0
#> 108 18.29 1 39 0 1
#> 124 9.73 1 NA 1 0
#> 108.1 18.29 1 39 0 1
#> 51 18.23 1 83 0 1
#> 197 21.60 1 69 1 0
#> 29 15.45 1 68 1 0
#> 169 22.41 1 46 0 0
#> 14 12.89 1 21 0 0
#> 51.1 18.23 1 83 0 1
#> 42 12.43 1 49 0 1
#> 140 12.68 1 59 1 0
#> 89.1 11.44 1 NA 0 0
#> 107 11.18 1 54 1 0
#> 77 7.27 1 67 0 1
#> 108.2 18.29 1 39 0 1
#> 192 16.44 1 31 1 0
#> 85 16.44 1 36 0 0
#> 179.1 18.63 1 42 0 0
#> 133 14.65 1 57 0 0
#> 183 9.24 1 67 1 0
#> 8.1 18.43 1 32 0 0
#> 183.1 9.24 1 67 1 0
#> 23 16.92 1 61 0 0
#> 169.1 22.41 1 46 0 0
#> 5 16.43 1 51 0 1
#> 164 23.60 1 76 0 1
#> 139 21.49 1 63 1 0
#> 166 19.98 1 48 0 0
#> 158 20.14 1 74 1 0
#> 129 23.41 1 53 1 0
#> 57 14.46 1 45 0 1
#> 110 17.56 1 65 0 1
#> 50 10.02 1 NA 1 0
#> 85.1 16.44 1 36 0 0
#> 24 23.89 1 38 0 0
#> 107.1 11.18 1 54 1 0
#> 127 3.53 1 62 0 1
#> 25 6.32 1 34 1 0
#> 110.1 17.56 1 65 0 1
#> 110.2 17.56 1 65 0 1
#> 170 19.54 1 43 0 1
#> 139.1 21.49 1 63 1 0
#> 43 12.10 1 61 0 1
#> 188 16.16 1 46 0 1
#> 45 17.42 1 54 0 1
#> 180 14.82 1 37 0 0
#> 123 13.00 1 44 1 0
#> 85.2 16.44 1 36 0 0
#> 37 12.52 1 57 1 0
#> 81 14.06 1 34 0 0
#> 167 15.55 1 56 1 0
#> 51.2 18.23 1 83 0 1
#> 168 23.72 1 70 0 0
#> 114 13.68 1 NA 0 0
#> 37.1 12.52 1 57 1 0
#> 4 17.64 1 NA 0 1
#> 155 13.08 1 26 0 0
#> 134 17.81 1 47 1 0
#> 168.1 23.72 1 70 0 0
#> 91 5.33 1 61 0 1
#> 130 16.47 1 53 0 1
#> 139.2 21.49 1 63 1 0
#> 14.1 12.89 1 21 0 0
#> 36 21.19 1 48 0 1
#> 113 22.86 1 34 0 0
#> 92 22.92 1 47 0 1
#> 199.1 19.81 1 NA 0 1
#> 181 16.46 1 45 0 1
#> 86 23.81 1 58 0 1
#> 90 20.94 1 50 0 1
#> 93 10.33 1 52 0 1
#> 157 15.10 1 47 0 0
#> 45.1 17.42 1 54 0 1
#> 56 12.21 1 60 0 0
#> 180.1 14.82 1 37 0 0
#> 58.1 19.34 1 39 0 0
#> 133.1 14.65 1 57 0 0
#> 40 18.00 1 28 1 0
#> 56.1 12.21 1 60 0 0
#> 15 22.68 1 48 0 0
#> 107.2 11.18 1 54 1 0
#> 85.3 16.44 1 36 0 0
#> 129.1 23.41 1 53 1 0
#> 57.1 14.46 1 45 0 1
#> 16 8.71 1 71 0 1
#> 129.2 23.41 1 53 1 0
#> 41 18.02 1 40 1 0
#> 168.2 23.72 1 70 0 0
#> 155.1 13.08 1 26 0 0
#> 56.2 12.21 1 60 0 0
#> 117.1 17.46 1 26 0 1
#> 40.1 18.00 1 28 1 0
#> 159 10.55 1 50 0 1
#> 10 10.53 1 34 0 0
#> 179.2 18.63 1 42 0 0
#> 177 12.53 1 75 0 0
#> 85.4 16.44 1 36 0 0
#> 183.2 9.24 1 67 1 0
#> 153 21.33 1 55 1 0
#> 89.2 11.44 1 NA 0 0
#> 89.3 11.44 1 NA 0 0
#> 139.3 21.49 1 63 1 0
#> 133.2 14.65 1 57 0 0
#> 10.1 10.53 1 34 0 0
#> 188.1 16.16 1 46 0 1
#> 53 24.00 0 32 0 1
#> 126 24.00 0 48 0 0
#> 54 24.00 0 53 1 0
#> 54.1 24.00 0 53 1 0
#> 38 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 3 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 152 24.00 0 36 0 1
#> 141 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 73 24.00 0 NA 0 1
#> 72 24.00 0 40 0 1
#> 44 24.00 0 56 0 0
#> 196 24.00 0 19 0 0
#> 151 24.00 0 42 0 0
#> 33 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 80 24.00 0 41 0 0
#> 102 24.00 0 49 0 0
#> 121 24.00 0 57 1 0
#> 54.2 24.00 0 53 1 0
#> 33.1 24.00 0 53 0 0
#> 19 24.00 0 57 0 1
#> 35 24.00 0 51 0 0
#> 148 24.00 0 61 1 0
#> 28 24.00 0 67 1 0
#> 83 24.00 0 6 0 0
#> 73.1 24.00 0 NA 0 1
#> 74 24.00 0 43 0 1
#> 21 24.00 0 47 0 0
#> 165 24.00 0 47 0 0
#> 151.1 24.00 0 42 0 0
#> 143 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 53.1 24.00 0 32 0 1
#> 185 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 83.1 24.00 0 6 0 0
#> 102.1 24.00 0 49 0 0
#> 116 24.00 0 58 0 1
#> 67.1 24.00 0 25 0 0
#> 193 24.00 0 45 0 1
#> 102.2 24.00 0 49 0 0
#> 142 24.00 0 53 0 0
#> 80.1 24.00 0 41 0 0
#> 64 24.00 0 43 0 0
#> 95 24.00 0 68 0 1
#> 151.2 24.00 0 42 0 0
#> 161 24.00 0 45 0 0
#> 65 24.00 0 57 1 0
#> 95.1 24.00 0 68 0 1
#> 21.1 24.00 0 47 0 0
#> 176 24.00 0 43 0 1
#> 54.3 24.00 0 53 1 0
#> 120 24.00 0 68 0 1
#> 75 24.00 0 21 1 0
#> 67.2 24.00 0 25 0 0
#> 172 24.00 0 41 0 0
#> 193.1 24.00 0 45 0 1
#> 191 24.00 0 60 0 1
#> 33.2 24.00 0 53 0 0
#> 138 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 95.2 24.00 0 68 0 1
#> 137 24.00 0 45 1 0
#> 7 24.00 0 37 1 0
#> 120.1 24.00 0 68 0 1
#> 22 24.00 0 52 1 0
#> 71 24.00 0 51 0 0
#> 74.1 24.00 0 43 0 1
#> 112 24.00 0 61 0 0
#> 84 24.00 0 39 0 1
#> 11 24.00 0 42 0 1
#> 17 24.00 0 38 0 1
#> 11.1 24.00 0 42 0 1
#> 185.1 24.00 0 44 1 0
#> 22.1 24.00 0 52 1 0
#> 98 24.00 0 34 1 0
#> 198.1 24.00 0 66 0 1
#> 115 24.00 0 NA 1 0
#> 118 24.00 0 44 1 0
#> 17.1 24.00 0 38 0 1
#> 148.1 24.00 0 61 1 0
#> 146 24.00 0 63 1 0
#> 104 24.00 0 50 1 0
#> 141.1 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.930 NA NA NA
#> 2 age, Cure model 0.0258 NA NA NA
#> 3 grade_ii, Cure model -0.309 NA NA NA
#> 4 grade_iii, Cure model -0.126 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0127 NA NA NA
#> 2 grade_ii, Survival model 0.259 NA NA NA
#> 3 grade_iii, Survival model 0.352 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.93041 0.02584 -0.30927 -0.12589
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 251.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.93041199 0.02583984 -0.30926814 -0.12588558
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01271082 0.25884702 0.35170598
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0449822472 0.3016787034 0.1631012675 0.1231355457 0.1387271412
#> [6] 0.1803764954 0.1803764954 0.2061483721 0.0504946343 0.4816954163
#> [11] 0.0351839586 0.6393749943 0.2061483721 0.7170217974 0.6647706169
#> [16] 0.7844851363 0.9404134357 0.1803764954 0.3737786935 0.3737786935
#> [21] 0.1387271412 0.5284797562 0.8825241092 0.1631012675 0.8825241092
#> [26] 0.3420287662 0.0351839586 0.4366008824 0.0087848959 0.0562995753
#> [31] 0.1078925597 0.1005512448 0.0121670987 0.5645942183 0.2721483452
#> [36] 0.3737786935 0.0002453623 0.7844851363 0.9849944530 0.9552230576
#> [41] 0.2721483452 0.2721483452 0.1154694464 0.0562995753 0.7707022805
#> [46] 0.4478342067 0.3216736467 0.5049592490 0.6266680284 0.3737786935
#> [51] 0.6907600246 0.5891441658 0.4702500579 0.2061483721 0.0026829788
#> [56] 0.6907600246 0.6016421037 0.2623441535 0.0026829788 0.9700693116
#> [61] 0.3525336580 0.0562995753 0.6393749943 0.0865107051 0.0261543155
#> [66] 0.0220342874 0.3631254494 0.0012410139 0.0934657372 0.8682110740
#> [71] 0.4932656463 0.3216736467 0.7303336090 0.5049592490 0.1231355457
#> [76] 0.5284797562 0.2433027110 0.7303336090 0.0305164481 0.7844851363
#> [81] 0.3737786935 0.0121670987 0.5645942183 0.9256950058 0.0121670987
#> [86] 0.2336596557 0.0026829788 0.6016421037 0.7303336090 0.3016787034
#> [91] 0.2433027110 0.8258571748 0.8399439013 0.1387271412 0.6776887585
#> [96] 0.3737786935 0.8825241092 0.0796809364 0.0562995753 0.5284797562
#> [101] 0.8399439013 0.4478342067 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000
#>
#> $Time
#> 66 117 8 58 179 108 108.1 51 197 29 169 14 51.1
#> 22.13 17.46 18.43 19.34 18.63 18.29 18.29 18.23 21.60 15.45 22.41 12.89 18.23
#> 42 140 107 77 108.2 192 85 179.1 133 183 8.1 183.1 23
#> 12.43 12.68 11.18 7.27 18.29 16.44 16.44 18.63 14.65 9.24 18.43 9.24 16.92
#> 169.1 5 164 139 166 158 129 57 110 85.1 24 107.1 127
#> 22.41 16.43 23.60 21.49 19.98 20.14 23.41 14.46 17.56 16.44 23.89 11.18 3.53
#> 25 110.1 110.2 170 139.1 43 188 45 180 123 85.2 37 81
#> 6.32 17.56 17.56 19.54 21.49 12.10 16.16 17.42 14.82 13.00 16.44 12.52 14.06
#> 167 51.2 168 37.1 155 134 168.1 91 130 139.2 14.1 36 113
#> 15.55 18.23 23.72 12.52 13.08 17.81 23.72 5.33 16.47 21.49 12.89 21.19 22.86
#> 92 181 86 90 93 157 45.1 56 180.1 58.1 133.1 40 56.1
#> 22.92 16.46 23.81 20.94 10.33 15.10 17.42 12.21 14.82 19.34 14.65 18.00 12.21
#> 15 107.2 85.3 129.1 57.1 16 129.2 41 168.2 155.1 56.2 117.1 40.1
#> 22.68 11.18 16.44 23.41 14.46 8.71 23.41 18.02 23.72 13.08 12.21 17.46 18.00
#> 159 10 179.2 177 85.4 183.2 153 139.3 133.2 10.1 188.1 53 126
#> 10.55 10.53 18.63 12.53 16.44 9.24 21.33 21.49 14.65 10.53 16.16 24.00 24.00
#> 54 54.1 38 144 3 109 152 141 131 72 44 196 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 198 80 102 121 54.2 33.1 19 35 148 28 83 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 165 151.1 143 67 53.1 185 48 34 83.1 102.1 116 67.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 102.2 142 80.1 64 95 151.2 161 65 95.1 21.1 176 54.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 75 67.2 172 193.1 191 33.2 138 173 95.2 137 7 120.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 71 74.1 112 84 11 17 11.1 185.1 22.1 98 198.1 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.1 148.1 146 104 141.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[45]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01253918 0.44961152 0.16892044
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.120293834 0.003329483 -0.196436723
#> grade_iii, Cure model
#> 0.527689509
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 128 20.35 1 35 0 1
#> 130 16.47 1 53 0 1
#> 10 10.53 1 34 0 0
#> 10.1 10.53 1 34 0 0
#> 190 20.81 1 42 1 0
#> 29 15.45 1 68 1 0
#> 184 17.77 1 38 0 0
#> 140 12.68 1 59 1 0
#> 26 15.77 1 49 0 1
#> 29.1 15.45 1 68 1 0
#> 187 9.92 1 39 1 0
#> 184.1 17.77 1 38 0 0
#> 154 12.63 1 20 1 0
#> 192 16.44 1 31 1 0
#> 5 16.43 1 51 0 1
#> 76 19.22 1 54 0 1
#> 110 17.56 1 65 0 1
#> 81 14.06 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 130.1 16.47 1 53 0 1
#> 42 12.43 1 49 0 1
#> 136 21.83 1 43 0 1
#> 13 14.34 1 54 0 1
#> 76.1 19.22 1 54 0 1
#> 155 13.08 1 26 0 0
#> 177 12.53 1 75 0 0
#> 167 15.55 1 56 1 0
#> 169 22.41 1 46 0 0
#> 45 17.42 1 54 0 1
#> 76.2 19.22 1 54 0 1
#> 14 12.89 1 21 0 0
#> 76.3 19.22 1 54 0 1
#> 136.1 21.83 1 43 0 1
#> 14.1 12.89 1 21 0 0
#> 18 15.21 1 49 1 0
#> 96 14.54 1 33 0 1
#> 100 16.07 1 60 0 0
#> 123 13.00 1 44 1 0
#> 133 14.65 1 57 0 0
#> 129 23.41 1 53 1 0
#> 24 23.89 1 38 0 0
#> 55 19.34 1 69 0 1
#> 197 21.60 1 69 1 0
#> 25 6.32 1 34 1 0
#> 41 18.02 1 40 1 0
#> 179 18.63 1 42 0 0
#> 4 17.64 1 NA 0 1
#> 18.1 15.21 1 49 1 0
#> 97 19.14 1 65 0 1
#> 45.1 17.42 1 54 0 1
#> 56 12.21 1 60 0 0
#> 128.1 20.35 1 35 0 1
#> 110.1 17.56 1 65 0 1
#> 169.1 22.41 1 46 0 0
#> 111 17.45 1 47 0 1
#> 15 22.68 1 48 0 0
#> 124 9.73 1 NA 1 0
#> 93 10.33 1 52 0 1
#> 91 5.33 1 61 0 1
#> 197.1 21.60 1 69 1 0
#> 68 20.62 1 44 0 0
#> 133.1 14.65 1 57 0 0
#> 77 7.27 1 67 0 1
#> 192.1 16.44 1 31 1 0
#> 93.1 10.33 1 52 0 1
#> 51 18.23 1 83 0 1
#> 26.1 15.77 1 49 0 1
#> 79 16.23 1 54 1 0
#> 164 23.60 1 76 0 1
#> 15.1 22.68 1 48 0 0
#> 175 21.91 1 43 0 0
#> 59 10.16 1 NA 1 0
#> 5.1 16.43 1 51 0 1
#> 127 3.53 1 62 0 1
#> 171 16.57 1 41 0 1
#> 10.2 10.53 1 34 0 0
#> 55.1 19.34 1 69 0 1
#> 130.2 16.47 1 53 0 1
#> 24.1 23.89 1 38 0 0
#> 15.2 22.68 1 48 0 0
#> 117 17.46 1 26 0 1
#> 133.2 14.65 1 57 0 0
#> 69 23.23 1 25 0 1
#> 70 7.38 1 30 1 0
#> 155.1 13.08 1 26 0 0
#> 158 20.14 1 74 1 0
#> 45.2 17.42 1 54 0 1
#> 170 19.54 1 43 0 1
#> 70.1 7.38 1 30 1 0
#> 92 22.92 1 47 0 1
#> 171.1 16.57 1 41 0 1
#> 55.2 19.34 1 69 0 1
#> 192.2 16.44 1 31 1 0
#> 88 18.37 1 47 0 0
#> 164.1 23.60 1 76 0 1
#> 52 10.42 1 52 0 1
#> 100.1 16.07 1 60 0 0
#> 60 13.15 1 38 1 0
#> 32 20.90 1 37 1 0
#> 68.1 20.62 1 44 0 0
#> 10.3 10.53 1 34 0 0
#> 97.1 19.14 1 65 0 1
#> 114 13.68 1 NA 0 0
#> 199 19.81 1 NA 0 1
#> 101 9.97 1 10 0 1
#> 180 14.82 1 37 0 0
#> 179.1 18.63 1 42 0 0
#> 85 16.44 1 36 0 0
#> 133.3 14.65 1 57 0 0
#> 59.1 10.16 1 NA 1 0
#> 157 15.10 1 47 0 0
#> 171.2 16.57 1 41 0 1
#> 82 24.00 0 34 0 0
#> 118 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 72 24.00 0 40 0 1
#> 137 24.00 0 45 1 0
#> 144 24.00 0 28 0 1
#> 165 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 94 24.00 0 51 0 1
#> 35 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 174 24.00 0 49 1 0
#> 152 24.00 0 36 0 1
#> 28 24.00 0 67 1 0
#> 95 24.00 0 68 0 1
#> 186 24.00 0 45 1 0
#> 46 24.00 0 71 0 0
#> 71 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 53 24.00 0 32 0 1
#> 35.1 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 94.1 24.00 0 51 0 1
#> 53.1 24.00 0 32 0 1
#> 172 24.00 0 41 0 0
#> 1 24.00 0 23 1 0
#> 120 24.00 0 68 0 1
#> 116.1 24.00 0 58 0 1
#> 104 24.00 0 50 1 0
#> 119 24.00 0 17 0 0
#> 17 24.00 0 38 0 1
#> 186.1 24.00 0 45 1 0
#> 65 24.00 0 57 1 0
#> 162 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 94.2 24.00 0 51 0 1
#> 162.1 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 186.2 24.00 0 45 1 0
#> 131 24.00 0 66 0 0
#> 67 24.00 0 25 0 0
#> 44 24.00 0 56 0 0
#> 48 24.00 0 31 1 0
#> 144.1 24.00 0 28 0 1
#> 137.1 24.00 0 45 1 0
#> 53.2 24.00 0 32 0 1
#> 83 24.00 0 6 0 0
#> 103 24.00 0 56 1 0
#> 84.1 24.00 0 39 0 1
#> 156 24.00 0 50 1 0
#> 98 24.00 0 34 1 0
#> 72.1 24.00 0 40 0 1
#> 156.1 24.00 0 50 1 0
#> 142 24.00 0 53 0 0
#> 146 24.00 0 63 1 0
#> 62 24.00 0 71 0 0
#> 147 24.00 0 76 1 0
#> 64 24.00 0 43 0 0
#> 64.1 24.00 0 43 0 0
#> 126 24.00 0 48 0 0
#> 144.2 24.00 0 28 0 1
#> 142.1 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 173 24.00 0 19 0 1
#> 27 24.00 0 63 1 0
#> 119.1 24.00 0 17 0 0
#> 62.1 24.00 0 71 0 0
#> 80 24.00 0 41 0 0
#> 135 24.00 0 58 1 0
#> 11 24.00 0 42 0 1
#> 47 24.00 0 38 0 1
#> 185 24.00 0 44 1 0
#> 94.3 24.00 0 51 0 1
#> 161.1 24.00 0 45 0 0
#> 119.2 24.00 0 17 0 0
#> 141 24.00 0 44 1 0
#> 27.1 24.00 0 63 1 0
#> 186.3 24.00 0 45 1 0
#> 148.1 24.00 0 61 1 0
#> 22 24.00 0 52 1 0
#> 80.1 24.00 0 41 0 0
#> 65.1 24.00 0 57 1 0
#> 95.1 24.00 0 68 0 1
#> 21.1 24.00 0 47 0 0
#> 131.1 24.00 0 66 0 0
#> 152.1 24.00 0 36 0 1
#> 151 24.00 0 42 0 0
#> 62.2 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.120 NA NA NA
#> 2 age, Cure model 0.00333 NA NA NA
#> 3 grade_ii, Cure model -0.196 NA NA NA
#> 4 grade_iii, Cure model 0.528 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0125 NA NA NA
#> 2 grade_ii, Survival model 0.450 NA NA NA
#> 3 grade_iii, Survival model 0.169 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.120294 0.003329 -0.196437 0.527690
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 266.1
#> Residual Deviance: 261.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.120293834 0.003329483 -0.196436723 0.527689509
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01253918 0.44961152 0.16892044
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.087737751 0.337106956 0.795351060 0.795351060 0.069890487 0.497709728
#> [7] 0.222216493 0.729959997 0.463708926 0.497709728 0.903129672 0.222216493
#> [13] 0.742940494 0.368158924 0.409171503 0.134054919 0.240178077 0.640851216
#> [19] 0.337106956 0.768938369 0.042658954 0.628279916 0.134054919 0.666172706
#> [25] 0.755871302 0.486246988 0.028495330 0.277994967 0.134054919 0.704343548
#> [31] 0.134054919 0.042658954 0.704343548 0.520718861 0.615808047 0.441558037
#> [37] 0.691525670 0.567621288 0.007676219 0.000606319 0.113402052 0.052999317
#> [43] 0.958140015 0.213325009 0.179191821 0.520718861 0.163193144 0.277994967
#> [49] 0.782085759 0.087737751 0.240178077 0.028495330 0.268340037 0.017463491
#> [55] 0.861937337 0.972003578 0.052999317 0.075737581 0.567621288 0.944271730
#> [61] 0.368158924 0.861937337 0.204452300 0.463708926 0.430633687 0.003034544
#> [67] 0.017463491 0.037546635 0.409171503 0.985956492 0.307135137 0.795351060
#> [73] 0.113402052 0.337106956 0.000606319 0.017463491 0.258802908 0.567621288
#> [79] 0.010759442 0.916933691 0.666172706 0.100141377 0.277994967 0.106707932
#> [85] 0.916933691 0.013972422 0.307135137 0.113402052 0.368158924 0.195798127
#> [91] 0.003034544 0.848295989 0.441558037 0.653508705 0.064079697 0.075737581
#> [97] 0.795351060 0.163193144 0.889333808 0.555705424 0.179191821 0.368158924
#> [103] 0.567621288 0.543883663 0.307135137 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000
#>
#> $Time
#> 128 130 10 10.1 190 29 184 140 26 29.1 187 184.1 154
#> 20.35 16.47 10.53 10.53 20.81 15.45 17.77 12.68 15.77 15.45 9.92 17.77 12.63
#> 192 5 76 110 81 130.1 42 136 13 76.1 155 177 167
#> 16.44 16.43 19.22 17.56 14.06 16.47 12.43 21.83 14.34 19.22 13.08 12.53 15.55
#> 169 45 76.2 14 76.3 136.1 14.1 18 96 100 123 133 129
#> 22.41 17.42 19.22 12.89 19.22 21.83 12.89 15.21 14.54 16.07 13.00 14.65 23.41
#> 24 55 197 25 41 179 18.1 97 45.1 56 128.1 110.1 169.1
#> 23.89 19.34 21.60 6.32 18.02 18.63 15.21 19.14 17.42 12.21 20.35 17.56 22.41
#> 111 15 93 91 197.1 68 133.1 77 192.1 93.1 51 26.1 79
#> 17.45 22.68 10.33 5.33 21.60 20.62 14.65 7.27 16.44 10.33 18.23 15.77 16.23
#> 164 15.1 175 5.1 127 171 10.2 55.1 130.2 24.1 15.2 117 133.2
#> 23.60 22.68 21.91 16.43 3.53 16.57 10.53 19.34 16.47 23.89 22.68 17.46 14.65
#> 69 70 155.1 158 45.2 170 70.1 92 171.1 55.2 192.2 88 164.1
#> 23.23 7.38 13.08 20.14 17.42 19.54 7.38 22.92 16.57 19.34 16.44 18.37 23.60
#> 52 100.1 60 32 68.1 10.3 97.1 101 180 179.1 85 133.3 157
#> 10.42 16.07 13.15 20.90 20.62 10.53 19.14 9.97 14.82 18.63 16.44 14.65 15.10
#> 171.2 82 118 148 72 137 144 165 12 94 35 21 174
#> 16.57 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 28 95 186 46 71 182 53 35.1 116 94.1 53.1 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 120 116.1 104 119 17 186.1 65 162 161 94.2 162.1 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.2 131 67 44 48 144.1 137.1 53.2 83 103 84.1 156 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 156.1 142 146 62 147 64 64.1 126 144.2 142.1 198 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 119.1 62.1 80 135 11 47 185 94.3 161.1 119.2 141 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.3 148.1 22 80.1 65.1 95.1 21.1 131.1 152.1 151 62.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[46]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01567848 1.15737529 0.86512760
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.15023603 0.02305968 0.24223671
#> grade_iii, Cure model
#> 0.66234346
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 97 19.14 1 65 0 1
#> 24 23.89 1 38 0 0
#> 36 21.19 1 48 0 1
#> 180 14.82 1 37 0 0
#> 170 19.54 1 43 0 1
#> 184 17.77 1 38 0 0
#> 45 17.42 1 54 0 1
#> 25 6.32 1 34 1 0
#> 140 12.68 1 59 1 0
#> 90 20.94 1 50 0 1
#> 30 17.43 1 78 0 0
#> 111 17.45 1 47 0 1
#> 91 5.33 1 61 0 1
#> 106 16.67 1 49 1 0
#> 149 8.37 1 33 1 0
#> 168 23.72 1 70 0 0
#> 167 15.55 1 56 1 0
#> 8 18.43 1 32 0 0
#> 97.1 19.14 1 65 0 1
#> 97.2 19.14 1 65 0 1
#> 51 18.23 1 83 0 1
#> 114 13.68 1 NA 0 0
#> 6 15.64 1 39 0 0
#> 55 19.34 1 69 0 1
#> 189 10.51 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 29 15.45 1 68 1 0
#> 170.1 19.54 1 43 0 1
#> 190 20.81 1 42 1 0
#> 167.1 15.55 1 56 1 0
#> 41 18.02 1 40 1 0
#> 136 21.83 1 43 0 1
#> 5 16.43 1 51 0 1
#> 101 9.97 1 10 0 1
#> 110 17.56 1 65 0 1
#> 184.1 17.77 1 38 0 0
#> 184.2 17.77 1 38 0 0
#> 187 9.92 1 39 1 0
#> 43 12.10 1 61 0 1
#> 169 22.41 1 46 0 0
#> 114.1 13.68 1 NA 0 0
#> 85 16.44 1 36 0 0
#> 79 16.23 1 54 1 0
#> 192 16.44 1 31 1 0
#> 43.1 12.10 1 61 0 1
#> 184.3 17.77 1 38 0 0
#> 139 21.49 1 63 1 0
#> 139.1 21.49 1 63 1 0
#> 60 13.15 1 38 1 0
#> 168.1 23.72 1 70 0 0
#> 52 10.42 1 52 0 1
#> 153 21.33 1 55 1 0
#> 175 21.91 1 43 0 0
#> 93 10.33 1 52 0 1
#> 107 11.18 1 54 1 0
#> 6.1 15.64 1 39 0 0
#> 125 15.65 1 67 1 0
#> 52.1 10.42 1 52 0 1
#> 51.1 18.23 1 83 0 1
#> 51.2 18.23 1 83 0 1
#> 113 22.86 1 34 0 0
#> 32 20.90 1 37 1 0
#> 8.1 18.43 1 32 0 0
#> 81 14.06 1 34 0 0
#> 81.1 14.06 1 34 0 0
#> 188 16.16 1 46 0 1
#> 187.1 9.92 1 39 1 0
#> 89 11.44 1 NA 0 0
#> 5.1 16.43 1 51 0 1
#> 68 20.62 1 44 0 0
#> 58 19.34 1 39 0 0
#> 136.1 21.83 1 43 0 1
#> 180.1 14.82 1 37 0 0
#> 113.1 22.86 1 34 0 0
#> 197 21.60 1 69 1 0
#> 49 12.19 1 48 1 0
#> 100 16.07 1 60 0 0
#> 15 22.68 1 48 0 0
#> 134 17.81 1 47 1 0
#> 40 18.00 1 28 1 0
#> 117 17.46 1 26 0 1
#> 189.1 10.51 1 NA 1 0
#> 106.1 16.67 1 49 1 0
#> 10 10.53 1 34 0 0
#> 154 12.63 1 20 1 0
#> 29.1 15.45 1 68 1 0
#> 97.3 19.14 1 65 0 1
#> 6.2 15.64 1 39 0 0
#> 36.1 21.19 1 48 0 1
#> 136.2 21.83 1 43 0 1
#> 41.1 18.02 1 40 1 0
#> 164 23.60 1 76 0 1
#> 110.1 17.56 1 65 0 1
#> 16 8.71 1 71 0 1
#> 97.4 19.14 1 65 0 1
#> 175.1 21.91 1 43 0 0
#> 78 23.88 1 43 0 0
#> 168.2 23.72 1 70 0 0
#> 68.1 20.62 1 44 0 0
#> 140.1 12.68 1 59 1 0
#> 179 18.63 1 42 0 0
#> 111.1 17.45 1 47 0 1
#> 91.1 5.33 1 61 0 1
#> 30.1 17.43 1 78 0 0
#> 158 20.14 1 74 1 0
#> 181 16.46 1 45 0 1
#> 45.1 17.42 1 54 0 1
#> 15.1 22.68 1 48 0 0
#> 179.1 18.63 1 42 0 0
#> 18 15.21 1 49 1 0
#> 189.2 10.51 1 NA 1 0
#> 169.1 22.41 1 46 0 0
#> 94 24.00 0 51 0 1
#> 137 24.00 0 45 1 0
#> 178 24.00 0 52 1 0
#> 82 24.00 0 34 0 0
#> 80 24.00 0 41 0 0
#> 48 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 178.1 24.00 0 52 1 0
#> 31 24.00 0 36 0 1
#> 162 24.00 0 51 0 0
#> 137.1 24.00 0 45 1 0
#> 35 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 83 24.00 0 6 0 0
#> 72 24.00 0 40 0 1
#> 132 24.00 0 55 0 0
#> 176 24.00 0 43 0 1
#> 172 24.00 0 41 0 0
#> 103 24.00 0 56 1 0
#> 112 24.00 0 61 0 0
#> 54 24.00 0 53 1 0
#> 33.1 24.00 0 53 0 0
#> 75 24.00 0 21 1 0
#> 148 24.00 0 61 1 0
#> 34 24.00 0 36 0 0
#> 33.2 24.00 0 53 0 0
#> 176.1 24.00 0 43 0 1
#> 67 24.00 0 25 0 0
#> 122 24.00 0 66 0 0
#> 80.1 24.00 0 41 0 0
#> 87 24.00 0 27 0 0
#> 83.1 24.00 0 6 0 0
#> 54.1 24.00 0 53 1 0
#> 84 24.00 0 39 0 1
#> 48.1 24.00 0 31 1 0
#> 82.1 24.00 0 34 0 0
#> 172.1 24.00 0 41 0 0
#> 196 24.00 0 19 0 0
#> 95 24.00 0 68 0 1
#> 135 24.00 0 58 1 0
#> 84.1 24.00 0 39 0 1
#> 115 24.00 0 NA 1 0
#> 160 24.00 0 31 1 0
#> 84.2 24.00 0 39 0 1
#> 161 24.00 0 45 0 0
#> 182 24.00 0 35 0 0
#> 95.1 24.00 0 68 0 1
#> 137.2 24.00 0 45 1 0
#> 131 24.00 0 66 0 0
#> 35.1 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 120 24.00 0 68 0 1
#> 102 24.00 0 49 0 0
#> 131.1 24.00 0 66 0 0
#> 131.2 24.00 0 66 0 0
#> 9 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 9.1 24.00 0 31 1 0
#> 178.2 24.00 0 52 1 0
#> 144 24.00 0 28 0 1
#> 200 24.00 0 64 0 0
#> 11 24.00 0 42 0 1
#> 126 24.00 0 48 0 0
#> 103.1 24.00 0 56 1 0
#> 35.2 24.00 0 51 0 0
#> 200.1 24.00 0 64 0 0
#> 163 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 7 24.00 0 37 1 0
#> 173 24.00 0 19 0 1
#> 67.1 24.00 0 25 0 0
#> 104 24.00 0 50 1 0
#> 126.1 24.00 0 48 0 0
#> 12 24.00 0 63 0 0
#> 119.1 24.00 0 17 0 0
#> 72.1 24.00 0 40 0 1
#> 196.1 24.00 0 19 0 0
#> 48.2 24.00 0 31 1 0
#> 172.2 24.00 0 41 0 0
#> 148.1 24.00 0 61 1 0
#> 44 24.00 0 56 0 0
#> 64 24.00 0 43 0 0
#> 53 24.00 0 32 0 1
#> 104.1 24.00 0 50 1 0
#> 160.1 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.15 NA NA NA
#> 2 age, Cure model 0.0231 NA NA NA
#> 3 grade_ii, Cure model 0.242 NA NA NA
#> 4 grade_iii, Cure model 0.662 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0157 NA NA NA
#> 2 grade_ii, Survival model 1.16 NA NA NA
#> 3 grade_iii, Survival model 0.865 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.15024 0.02306 0.24224 0.66234
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 255.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.15023603 0.02305968 0.24223671 0.66234346
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01567848 1.15737529 0.86512760
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.2798693383 0.0001945046 0.1573618790 0.7621873040 0.2421287279
#> [6] 0.4381327616 0.5495096166 0.9714184885 0.8132847739 0.1763547562
#> [11] 0.5288191303 0.5086845561 0.9809659101 0.5701856681 0.9617890185
#> [16] 0.0030645971 0.7116033817 0.3462694701 0.2798693383 0.2798693383
#> [21] 0.3667304983 0.6811472089 0.2607761987 0.2324587781 0.7318674958
#> [26] 0.2421287279 0.1954167392 0.7116033817 0.3979000026 0.0881253613
#> [31] 0.6208224962 0.9229365893 0.4779787088 0.4381327616 0.4381327616
#> [36] 0.9327811782 0.8534536559 0.0468939992 0.6007322971 0.6408688250
#> [41] 0.6007322971 0.8534536559 0.4381327616 0.1277510192 0.1277510192
#> [46] 0.8030474040 0.0030645971 0.8931720977 0.1474140991 0.0659247989
#> [51] 0.9129825755 0.8732741269 0.6811472089 0.6710497267 0.8931720977
#> [56] 0.3667304983 0.3667304983 0.0188068116 0.1860762549 0.3462694701
#> [61] 0.7825071490 0.7825071490 0.6509139164 0.9327811782 0.6208224962
#> [66] 0.2044772131 0.2607761987 0.0881253613 0.7621873040 0.0188068116
#> [71] 0.1171997054 0.8435054832 0.6609350734 0.0311764357 0.4282316880
#> [76] 0.4182095090 0.4984597485 0.5701856681 0.8831999580 0.8334984180
#> [81] 0.7318674958 0.2798693383 0.6811472089 0.1573618790 0.0881253613
#> [86] 0.3979000026 0.0131304730 0.4779787088 0.9520723397 0.2798693383
#> [91] 0.0659247989 0.0011938100 0.0030645971 0.2044772131 0.8132847739
#> [96] 0.3262747493 0.5086845561 0.9809659101 0.5288191303 0.2229970056
#> [101] 0.5905112274 0.5495096166 0.0311764357 0.3262747493 0.7520781901
#> [106] 0.0468939992 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 97 24 36 180 170 184 45 25 140 90 30 111 91
#> 19.14 23.89 21.19 14.82 19.54 17.77 17.42 6.32 12.68 20.94 17.43 17.45 5.33
#> 106 149 168 167 8 97.1 97.2 51 6 55 166 29 170.1
#> 16.67 8.37 23.72 15.55 18.43 19.14 19.14 18.23 15.64 19.34 19.98 15.45 19.54
#> 190 167.1 41 136 5 101 110 184.1 184.2 187 43 169 85
#> 20.81 15.55 18.02 21.83 16.43 9.97 17.56 17.77 17.77 9.92 12.10 22.41 16.44
#> 79 192 43.1 184.3 139 139.1 60 168.1 52 153 175 93 107
#> 16.23 16.44 12.10 17.77 21.49 21.49 13.15 23.72 10.42 21.33 21.91 10.33 11.18
#> 6.1 125 52.1 51.1 51.2 113 32 8.1 81 81.1 188 187.1 5.1
#> 15.64 15.65 10.42 18.23 18.23 22.86 20.90 18.43 14.06 14.06 16.16 9.92 16.43
#> 68 58 136.1 180.1 113.1 197 49 100 15 134 40 117 106.1
#> 20.62 19.34 21.83 14.82 22.86 21.60 12.19 16.07 22.68 17.81 18.00 17.46 16.67
#> 10 154 29.1 97.3 6.2 36.1 136.2 41.1 164 110.1 16 97.4 175.1
#> 10.53 12.63 15.45 19.14 15.64 21.19 21.83 18.02 23.60 17.56 8.71 19.14 21.91
#> 78 168.2 68.1 140.1 179 111.1 91.1 30.1 158 181 45.1 15.1 179.1
#> 23.88 23.72 20.62 12.68 18.63 17.45 5.33 17.43 20.14 16.46 17.42 22.68 18.63
#> 18 169.1 94 137 178 82 80 48 33 198 178.1 31 162
#> 15.21 22.41 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 35 47 83 72 132 176 172 103 112 54 33.1 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 34 33.2 176.1 67 122 80.1 87 83.1 54.1 84 48.1 82.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 196 95 135 84.1 160 84.2 161 182 95.1 137.2 131 35.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 120 102 131.1 131.2 9 185 119 9.1 178.2 144 200 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 103.1 35.2 200.1 163 165 7 173 67.1 104 126.1 12 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 196.1 48.2 172.2 148.1 44 64 53 104.1 160.1 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[47]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005460897 0.502838028 0.534003378
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.440932197 0.004586378 0.663170171
#> grade_iii, Cure model
#> 1.083919251
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 180 14.82 1 37 0 0
#> 157 15.10 1 47 0 0
#> 69 23.23 1 25 0 1
#> 78 23.88 1 43 0 0
#> 66 22.13 1 53 0 0
#> 128 20.35 1 35 0 1
#> 63 22.77 1 31 1 0
#> 68 20.62 1 44 0 0
#> 159 10.55 1 50 0 1
#> 153 21.33 1 55 1 0
#> 130 16.47 1 53 0 1
#> 184 17.77 1 38 0 0
#> 166 19.98 1 48 0 0
#> 179 18.63 1 42 0 0
#> 5 16.43 1 51 0 1
#> 4 17.64 1 NA 0 1
#> 57 14.46 1 45 0 1
#> 36 21.19 1 48 0 1
#> 76 19.22 1 54 0 1
#> 13 14.34 1 54 0 1
#> 170 19.54 1 43 0 1
#> 58 19.34 1 39 0 0
#> 140 12.68 1 59 1 0
#> 77 7.27 1 67 0 1
#> 113 22.86 1 34 0 0
#> 133 14.65 1 57 0 0
#> 197 21.60 1 69 1 0
#> 89 11.44 1 NA 0 0
#> 180.1 14.82 1 37 0 0
#> 153.1 21.33 1 55 1 0
#> 106 16.67 1 49 1 0
#> 187 9.92 1 39 1 0
#> 169 22.41 1 46 0 0
#> 167 15.55 1 56 1 0
#> 66.1 22.13 1 53 0 0
#> 167.1 15.55 1 56 1 0
#> 49 12.19 1 48 1 0
#> 168 23.72 1 70 0 0
#> 66.2 22.13 1 53 0 0
#> 149 8.37 1 33 1 0
#> 171 16.57 1 41 0 1
#> 190 20.81 1 42 1 0
#> 55 19.34 1 69 0 1
#> 14 12.89 1 21 0 0
#> 125 15.65 1 67 1 0
#> 187.1 9.92 1 39 1 0
#> 10 10.53 1 34 0 0
#> 85 16.44 1 36 0 0
#> 171.1 16.57 1 41 0 1
#> 29 15.45 1 68 1 0
#> 190.1 20.81 1 42 1 0
#> 85.1 16.44 1 36 0 0
#> 125.1 15.65 1 67 1 0
#> 117 17.46 1 26 0 1
#> 56 12.21 1 60 0 0
#> 108 18.29 1 39 0 1
#> 49.1 12.19 1 48 1 0
#> 159.1 10.55 1 50 0 1
#> 101 9.97 1 10 0 1
#> 110 17.56 1 65 0 1
#> 134 17.81 1 47 1 0
#> 57.1 14.46 1 45 0 1
#> 192 16.44 1 31 1 0
#> 127 3.53 1 62 0 1
#> 18 15.21 1 49 1 0
#> 194 22.40 1 38 0 1
#> 69.1 23.23 1 25 0 1
#> 105 19.75 1 60 0 0
#> 66.3 22.13 1 53 0 0
#> 23 16.92 1 61 0 0
#> 39 15.59 1 37 0 1
#> 78.1 23.88 1 43 0 0
#> 180.2 14.82 1 37 0 0
#> 37 12.52 1 57 1 0
#> 159.2 10.55 1 50 0 1
#> 10.1 10.53 1 34 0 0
#> 40 18.00 1 28 1 0
#> 56.1 12.21 1 60 0 0
#> 180.3 14.82 1 37 0 0
#> 99 21.19 1 38 0 1
#> 123 13.00 1 44 1 0
#> 194.1 22.40 1 38 0 1
#> 4.1 17.64 1 NA 0 1
#> 96 14.54 1 33 0 1
#> 63.1 22.77 1 31 1 0
#> 149.1 8.37 1 33 1 0
#> 189 10.51 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 32 20.90 1 37 1 0
#> 26 15.77 1 49 0 1
#> 100 16.07 1 60 0 0
#> 108.1 18.29 1 39 0 1
#> 184.1 17.77 1 38 0 0
#> 61 10.12 1 36 0 1
#> 154 12.63 1 20 1 0
#> 171.2 16.57 1 41 0 1
#> 36.1 21.19 1 48 0 1
#> 4.2 17.64 1 NA 0 1
#> 96.1 14.54 1 33 0 1
#> 66.4 22.13 1 53 0 0
#> 50 10.02 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 167.2 15.55 1 56 1 0
#> 113.1 22.86 1 34 0 0
#> 107 11.18 1 54 1 0
#> 129 23.41 1 53 1 0
#> 16 8.71 1 71 0 1
#> 154.1 12.63 1 20 1 0
#> 158 20.14 1 74 1 0
#> 85.2 16.44 1 36 0 0
#> 166.1 19.98 1 48 0 0
#> 159.3 10.55 1 50 0 1
#> 142 24.00 0 53 0 0
#> 196 24.00 0 19 0 0
#> 62 24.00 0 71 0 0
#> 112 24.00 0 61 0 0
#> 3 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 75 24.00 0 21 1 0
#> 147 24.00 0 76 1 0
#> 141 24.00 0 44 1 0
#> 75.1 24.00 0 21 1 0
#> 87 24.00 0 27 0 0
#> 115 24.00 0 NA 1 0
#> 131 24.00 0 66 0 0
#> 74 24.00 0 43 0 1
#> 46 24.00 0 71 0 0
#> 115.1 24.00 0 NA 1 0
#> 156 24.00 0 50 1 0
#> 200 24.00 0 64 0 0
#> 75.2 24.00 0 21 1 0
#> 64 24.00 0 43 0 0
#> 82 24.00 0 34 0 0
#> 17 24.00 0 38 0 1
#> 64.1 24.00 0 43 0 0
#> 142.1 24.00 0 53 0 0
#> 143 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 67 24.00 0 25 0 0
#> 12 24.00 0 63 0 0
#> 62.1 24.00 0 71 0 0
#> 115.2 24.00 0 NA 1 0
#> 173 24.00 0 19 0 1
#> 151 24.00 0 42 0 0
#> 84 24.00 0 39 0 1
#> 182 24.00 0 35 0 0
#> 172 24.00 0 41 0 0
#> 173.1 24.00 0 19 0 1
#> 119 24.00 0 17 0 0
#> 198 24.00 0 66 0 1
#> 174.1 24.00 0 49 1 0
#> 44 24.00 0 56 0 0
#> 160 24.00 0 31 1 0
#> 122.1 24.00 0 66 0 0
#> 87.1 24.00 0 27 0 0
#> 119.1 24.00 0 17 0 0
#> 73 24.00 0 NA 0 1
#> 162 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 62.2 24.00 0 71 0 0
#> 152 24.00 0 36 0 1
#> 191 24.00 0 60 0 1
#> 200.1 24.00 0 64 0 0
#> 141.1 24.00 0 44 1 0
#> 119.2 24.00 0 17 0 0
#> 135 24.00 0 58 1 0
#> 115.3 24.00 0 NA 1 0
#> 109 24.00 0 48 0 0
#> 112.1 24.00 0 61 0 0
#> 102 24.00 0 49 0 0
#> 173.2 24.00 0 19 0 1
#> 48 24.00 0 31 1 0
#> 147.1 24.00 0 76 1 0
#> 160.1 24.00 0 31 1 0
#> 28.1 24.00 0 67 1 0
#> 173.3 24.00 0 19 0 1
#> 73.1 24.00 0 NA 0 1
#> 95 24.00 0 68 0 1
#> 141.2 24.00 0 44 1 0
#> 142.2 24.00 0 53 0 0
#> 151.1 24.00 0 42 0 0
#> 142.3 24.00 0 53 0 0
#> 196.1 24.00 0 19 0 0
#> 67.1 24.00 0 25 0 0
#> 17.1 24.00 0 38 0 1
#> 173.4 24.00 0 19 0 1
#> 3.1 24.00 0 31 1 0
#> 172.1 24.00 0 41 0 0
#> 35 24.00 0 51 0 0
#> 72 24.00 0 40 0 1
#> 94 24.00 0 51 0 1
#> 135.1 24.00 0 58 1 0
#> 103 24.00 0 56 1 0
#> 82.1 24.00 0 34 0 0
#> 122.2 24.00 0 66 0 0
#> 126 24.00 0 48 0 0
#> 80 24.00 0 41 0 0
#> 35.1 24.00 0 51 0 0
#> 193 24.00 0 45 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.441 NA NA NA
#> 2 age, Cure model 0.00459 NA NA NA
#> 3 grade_ii, Cure model 0.663 NA NA NA
#> 4 grade_iii, Cure model 1.08 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00546 NA NA NA
#> 2 grade_ii, Survival model 0.503 NA NA NA
#> 3 grade_iii, Survival model 0.534 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.440932 0.004586 0.663170 1.083919
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 257.6
#> Residual Deviance: 248.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.440932197 0.004586378 0.663170171 1.083919251
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005460897 0.502838028 0.534003378
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.78767983 0.78143948 0.17049211 0.05123669 0.31908927 0.48529375
#> [7] 0.24375335 0.47558114 0.92198152 0.39250045 0.67445433 0.60659082
#> [13] 0.50405112 0.56583642 0.70930659 0.83046871 0.41526362 0.55734872
#> [19] 0.84238077 0.53126130 0.54016744 0.86585187 0.98990904 0.20777112
#> [25] 0.81217446 0.38004548 0.78767983 0.39250045 0.64539896 0.96421475
#> [31] 0.27528882 0.74986708 0.31908927 0.74986708 0.90549287 0.11297541
#> [37] 0.31908927 0.97973257 0.65293658 0.45624818 0.54016744 0.86002047
#> [43] 0.73000211 0.96421475 0.94309116 0.68160630 0.65293658 0.76887043
#> [49] 0.45624818 0.68160630 0.73000211 0.63008021 0.89432873 0.57429143
#> [55] 0.90549287 0.92198152 0.95895966 0.62231121 0.59863115 0.83046871
#> [61] 0.68160630 0.99497234 0.77518453 0.29126705 0.17049211 0.52217897
#> [67] 0.31908927 0.63775777 0.74326841 0.05123669 0.78767983 0.88303076
#> [73] 0.92198152 0.94309116 0.59054929 0.89432873 0.78767983 0.41526362
#> [79] 0.85418426 0.29126705 0.81835141 0.24375335 0.97973257 0.84830376
#> [85] 0.44600339 0.72316584 0.71624921 0.57429143 0.60659082 0.95368139
#> [91] 0.87163335 0.65293658 0.41526362 0.81835141 0.31908927 0.88870181
#> [97] 0.74986708 0.20777112 0.91650108 0.14510909 0.97457845 0.87163335
#> [103] 0.49480366 0.68160630 0.50405112 0.92198152 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 180 157 69 78 66 128 63 68 159 153 130 184 166
#> 14.82 15.10 23.23 23.88 22.13 20.35 22.77 20.62 10.55 21.33 16.47 17.77 19.98
#> 179 5 57 36 76 13 170 58 140 77 113 133 197
#> 18.63 16.43 14.46 21.19 19.22 14.34 19.54 19.34 12.68 7.27 22.86 14.65 21.60
#> 180.1 153.1 106 187 169 167 66.1 167.1 49 168 66.2 149 171
#> 14.82 21.33 16.67 9.92 22.41 15.55 22.13 15.55 12.19 23.72 22.13 8.37 16.57
#> 190 55 14 125 187.1 10 85 171.1 29 190.1 85.1 125.1 117
#> 20.81 19.34 12.89 15.65 9.92 10.53 16.44 16.57 15.45 20.81 16.44 15.65 17.46
#> 56 108 49.1 159.1 101 110 134 57.1 192 127 18 194 69.1
#> 12.21 18.29 12.19 10.55 9.97 17.56 17.81 14.46 16.44 3.53 15.21 22.40 23.23
#> 105 66.3 23 39 78.1 180.2 37 159.2 10.1 40 56.1 180.3 99
#> 19.75 22.13 16.92 15.59 23.88 14.82 12.52 10.55 10.53 18.00 12.21 14.82 21.19
#> 123 194.1 96 63.1 149.1 60 32 26 100 108.1 184.1 61 154
#> 13.00 22.40 14.54 22.77 8.37 13.15 20.90 15.77 16.07 18.29 17.77 10.12 12.63
#> 171.2 36.1 96.1 66.4 42 167.2 113.1 107 129 16 154.1 158 85.2
#> 16.57 21.19 14.54 22.13 12.43 15.55 22.86 11.18 23.41 8.71 12.63 20.14 16.44
#> 166.1 159.3 142 196 62 112 3 122 174 75 147 141 75.1
#> 19.98 10.55 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 131 74 46 156 200 75.2 64 82 17 64.1 142.1 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 67 12 62.1 173 151 84 182 172 173.1 119 198 174.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 160 122.1 87.1 119.1 162 65 62.2 152 191 200.1 141.1 119.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 109 112.1 102 173.2 48 147.1 160.1 28.1 173.3 95 141.2 142.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 142.3 196.1 67.1 17.1 173.4 3.1 172.1 35 72 94 135.1 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.1 122.2 126 80 35.1 193
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[48]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001010466 0.322881433 0.497859379
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.198218011 -0.001598608 0.498200661
#> grade_iii, Cure model
#> 0.866675272
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 32 20.90 1 37 1 0
#> 167 15.55 1 56 1 0
#> 194 22.40 1 38 0 1
#> 41 18.02 1 40 1 0
#> 81 14.06 1 34 0 0
#> 45 17.42 1 54 0 1
#> 114 13.68 1 NA 0 0
#> 16 8.71 1 71 0 1
#> 189 10.51 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 89 11.44 1 NA 0 0
#> 41.1 18.02 1 40 1 0
#> 183 9.24 1 67 1 0
#> 140 12.68 1 59 1 0
#> 10 10.53 1 34 0 0
#> 184 17.77 1 38 0 0
#> 30 17.43 1 78 0 0
#> 88 18.37 1 47 0 0
#> 194.1 22.40 1 38 0 1
#> 170 19.54 1 43 0 1
#> 76 19.22 1 54 0 1
#> 43 12.10 1 61 0 1
#> 29 15.45 1 68 1 0
#> 68 20.62 1 44 0 0
#> 5 16.43 1 51 0 1
#> 18 15.21 1 49 1 0
#> 43.1 12.10 1 61 0 1
#> 63 22.77 1 31 1 0
#> 58 19.34 1 39 0 0
#> 40 18.00 1 28 1 0
#> 32.1 20.90 1 37 1 0
#> 24 23.89 1 38 0 0
#> 81.1 14.06 1 34 0 0
#> 43.2 12.10 1 61 0 1
#> 52 10.42 1 52 0 1
#> 97 19.14 1 65 0 1
#> 133 14.65 1 57 0 0
#> 26 15.77 1 49 0 1
#> 15 22.68 1 48 0 0
#> 23 16.92 1 61 0 0
#> 6 15.64 1 39 0 0
#> 86 23.81 1 58 0 1
#> 90 20.94 1 50 0 1
#> 101 9.97 1 10 0 1
#> 128 20.35 1 35 0 1
#> 114.1 13.68 1 NA 0 0
#> 45.1 17.42 1 54 0 1
#> 166 19.98 1 48 0 0
#> 101.1 9.97 1 10 0 1
#> 50 10.02 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 69 23.23 1 25 0 1
#> 114.2 13.68 1 NA 0 0
#> 91 5.33 1 61 0 1
#> 51 18.23 1 83 0 1
#> 6.1 15.64 1 39 0 0
#> 197 21.60 1 69 1 0
#> 79 16.23 1 54 1 0
#> 149 8.37 1 33 1 0
#> 129 23.41 1 53 1 0
#> 24.1 23.89 1 38 0 0
#> 129.1 23.41 1 53 1 0
#> 96 14.54 1 33 0 1
#> 40.1 18.00 1 28 1 0
#> 140.1 12.68 1 59 1 0
#> 149.1 8.37 1 33 1 0
#> 181 16.46 1 45 0 1
#> 154 12.63 1 20 1 0
#> 5.1 16.43 1 51 0 1
#> 192 16.44 1 31 1 0
#> 58.1 19.34 1 39 0 0
#> 157 15.10 1 47 0 0
#> 189.1 10.51 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 113 22.86 1 34 0 0
#> 127 3.53 1 62 0 1
#> 99 21.19 1 38 0 1
#> 150 20.33 1 48 0 0
#> 197.1 21.60 1 69 1 0
#> 39 15.59 1 37 0 1
#> 69.1 23.23 1 25 0 1
#> 110 17.56 1 65 0 1
#> 24.2 23.89 1 38 0 0
#> 52.1 10.42 1 52 0 1
#> 40.2 18.00 1 28 1 0
#> 25 6.32 1 34 1 0
#> 15.1 22.68 1 48 0 0
#> 29.1 15.45 1 68 1 0
#> 59 10.16 1 NA 1 0
#> 184.1 17.77 1 38 0 0
#> 166.1 19.98 1 48 0 0
#> 139 21.49 1 63 1 0
#> 123 13.00 1 44 1 0
#> 139.1 21.49 1 63 1 0
#> 96.1 14.54 1 33 0 1
#> 154.1 12.63 1 20 1 0
#> 10.1 10.53 1 34 0 0
#> 189.2 10.51 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 43.3 12.10 1 61 0 1
#> 139.2 21.49 1 63 1 0
#> 129.2 23.41 1 53 1 0
#> 107 11.18 1 54 1 0
#> 66 22.13 1 53 0 0
#> 197.2 21.60 1 69 1 0
#> 149.2 8.37 1 33 1 0
#> 26.1 15.77 1 49 0 1
#> 166.2 19.98 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 108 18.29 1 39 0 1
#> 110.1 17.56 1 65 0 1
#> 68.1 20.62 1 44 0 0
#> 28 24.00 0 67 1 0
#> 142 24.00 0 53 0 0
#> 172 24.00 0 41 0 0
#> 132 24.00 0 55 0 0
#> 141 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 11 24.00 0 42 0 1
#> 11.1 24.00 0 42 0 1
#> 142.1 24.00 0 53 0 0
#> 119 24.00 0 17 0 0
#> 72 24.00 0 40 0 1
#> 27 24.00 0 63 1 0
#> 119.1 24.00 0 17 0 0
#> 142.2 24.00 0 53 0 0
#> 165 24.00 0 47 0 0
#> 176 24.00 0 43 0 1
#> 151 24.00 0 42 0 0
#> 9 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 146 24.00 0 63 1 0
#> 28.1 24.00 0 67 1 0
#> 74 24.00 0 43 0 1
#> 12 24.00 0 63 0 0
#> 186 24.00 0 45 1 0
#> 104 24.00 0 50 1 0
#> 152 24.00 0 36 0 1
#> 17 24.00 0 38 0 1
#> 82 24.00 0 34 0 0
#> 135 24.00 0 58 1 0
#> 146.1 24.00 0 63 1 0
#> 47 24.00 0 38 0 1
#> 33 24.00 0 53 0 0
#> 62 24.00 0 71 0 0
#> 200 24.00 0 64 0 0
#> 121 24.00 0 57 1 0
#> 9.1 24.00 0 31 1 0
#> 142.3 24.00 0 53 0 0
#> 131 24.00 0 66 0 0
#> 44 24.00 0 56 0 0
#> 116 24.00 0 58 0 1
#> 146.2 24.00 0 63 1 0
#> 80 24.00 0 41 0 0
#> 198.1 24.00 0 66 0 1
#> 103 24.00 0 56 1 0
#> 72.1 24.00 0 40 0 1
#> 27.1 24.00 0 63 1 0
#> 152.1 24.00 0 36 0 1
#> 53 24.00 0 32 0 1
#> 193 24.00 0 45 0 1
#> 87 24.00 0 27 0 0
#> 80.1 24.00 0 41 0 0
#> 165.1 24.00 0 47 0 0
#> 12.1 24.00 0 63 0 0
#> 9.2 24.00 0 31 1 0
#> 142.4 24.00 0 53 0 0
#> 17.1 24.00 0 38 0 1
#> 11.2 24.00 0 42 0 1
#> 19 24.00 0 57 0 1
#> 193.1 24.00 0 45 0 1
#> 165.2 24.00 0 47 0 0
#> 74.1 24.00 0 43 0 1
#> 3 24.00 0 31 1 0
#> 119.2 24.00 0 17 0 0
#> 138 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 20.1 24.00 0 46 1 0
#> 54 24.00 0 53 1 0
#> 163 24.00 0 66 0 0
#> 73 24.00 0 NA 0 1
#> 20.2 24.00 0 46 1 0
#> 160 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 12.2 24.00 0 63 0 0
#> 21 24.00 0 47 0 0
#> 163.1 24.00 0 66 0 0
#> 75 24.00 0 21 1 0
#> 21.1 24.00 0 47 0 0
#> 142.5 24.00 0 53 0 0
#> 35 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 119.3 24.00 0 17 0 0
#> 102 24.00 0 49 0 0
#> 186.1 24.00 0 45 1 0
#> 137 24.00 0 45 1 0
#> 116.1 24.00 0 58 0 1
#> 102.1 24.00 0 49 0 0
#> 65 24.00 0 57 1 0
#> 126 24.00 0 48 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.198 NA NA NA
#> 2 age, Cure model -0.00160 NA NA NA
#> 3 grade_ii, Cure model 0.498 NA NA NA
#> 4 grade_iii, Cure model 0.867 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00101 NA NA NA
#> 2 grade_ii, Survival model 0.323 NA NA NA
#> 3 grade_iii, Survival model 0.498 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.198218 -0.001599 0.498201 0.866675
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 255 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.198218011 -0.001598608 0.498200661 0.866675272
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001010466 0.322881433 0.497859379
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.36240646 0.74652569 0.23877446 0.52875945 0.80751946 0.62533512
#> [7] 0.95204982 0.60811783 0.52875945 0.94506004 0.83754872 0.90268694
#> [13] 0.57316389 0.61673140 0.50061222 0.23877446 0.45219831 0.48143428
#> [19] 0.86706762 0.75428597 0.38264357 0.66715818 0.76957665 0.86706762
#> [25] 0.19886991 0.46202419 0.54682900 0.36240646 0.03543833 0.80751946
#> [31] 0.86706762 0.91696562 0.49109409 0.78487148 0.69951064 0.21251611
#> [37] 0.64208664 0.72309880 0.09277008 0.35188423 0.93108296 0.40283240
#> [43] 0.62533512 0.42290949 0.93108296 0.71523464 0.15770387 0.98637683
#> [49] 0.51950645 0.72309880 0.27558030 0.68336423 0.95900043 0.11395502
#> [55] 0.03543833 0.11395502 0.79251265 0.54682900 0.83754872 0.95900043
#> [61] 0.65051072 0.85236047 0.66715818 0.65885680 0.46202419 0.77722589
#> [67] 0.82251654 0.18481432 0.99320597 0.34112708 0.41287701 0.27558030
#> [73] 0.73872801 0.15770387 0.59083645 0.03543833 0.91696562 0.54682900
#> [79] 0.97951205 0.21251611 0.75428597 0.57316389 0.42290949 0.30917046
#> [85] 0.83004773 0.30917046 0.79251265 0.85236047 0.90268694 0.69147153
#> [91] 0.86706762 0.30917046 0.11395502 0.89551516 0.26313606 0.27558030
#> [97] 0.95900043 0.69951064 0.42290949 0.51012155 0.59083645 0.38264357
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 32 167 194 41 81 45 16 111 41.1 183 140 10 184
#> 20.90 15.55 22.40 18.02 14.06 17.42 8.71 17.45 18.02 9.24 12.68 10.53 17.77
#> 30 88 194.1 170 76 43 29 68 5 18 43.1 63 58
#> 17.43 18.37 22.40 19.54 19.22 12.10 15.45 20.62 16.43 15.21 12.10 22.77 19.34
#> 40 32.1 24 81.1 43.2 52 97 133 26 15 23 6 86
#> 18.00 20.90 23.89 14.06 12.10 10.42 19.14 14.65 15.77 22.68 16.92 15.64 23.81
#> 90 101 128 45.1 166 101.1 125 69 91 51 6.1 197 79
#> 20.94 9.97 20.35 17.42 19.98 9.97 15.65 23.23 5.33 18.23 15.64 21.60 16.23
#> 149 129 24.1 129.1 96 40.1 140.1 149.1 181 154 5.1 192 58.1
#> 8.37 23.41 23.89 23.41 14.54 18.00 12.68 8.37 16.46 12.63 16.43 16.44 19.34
#> 157 155 113 127 99 150 197.1 39 69.1 110 24.2 52.1 40.2
#> 15.10 13.08 22.86 3.53 21.19 20.33 21.60 15.59 23.23 17.56 23.89 10.42 18.00
#> 25 15.1 29.1 184.1 166.1 139 123 139.1 96.1 154.1 10.1 188 43.3
#> 6.32 22.68 15.45 17.77 19.98 21.49 13.00 21.49 14.54 12.63 10.53 16.16 12.10
#> 139.2 129.2 107 66 197.2 149.2 26.1 166.2 108 110.1 68.1 28 142
#> 21.49 23.41 11.18 22.13 21.60 8.37 15.77 19.98 18.29 17.56 20.62 24.00 24.00
#> 172 132 141 67 11 11.1 142.1 119 72 27 119.1 142.2 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 151 9 198 146 28.1 74 12 186 104 152 17 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 146.1 47 33 62 200 121 9.1 142.3 131 44 116 146.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 198.1 103 72.1 27.1 152.1 53 193 87 80.1 165.1 12.1 9.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.4 17.1 11.2 19 193.1 165.2 74.1 3 119.2 138 20 20.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 20.2 160 83 12.2 21 163.1 75 21.1 142.5 35 7 119.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 186.1 137 116.1 102.1 65 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[49]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004314238 0.162456994 0.243604340
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.32946502 0.02414302 0.17559326
#> grade_iii, Cure model
#> 0.86595371
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 56 12.21 1 60 0 0
#> 150 20.33 1 48 0 0
#> 8 18.43 1 32 0 0
#> 130 16.47 1 53 0 1
#> 105 19.75 1 60 0 0
#> 133 14.65 1 57 0 0
#> 59 10.16 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 41 18.02 1 40 1 0
#> 57 14.46 1 45 0 1
#> 125 15.65 1 67 1 0
#> 61 10.12 1 36 0 1
#> 76 19.22 1 54 0 1
#> 45 17.42 1 54 0 1
#> 49 12.19 1 48 1 0
#> 181 16.46 1 45 0 1
#> 108 18.29 1 39 0 1
#> 155 13.08 1 26 0 0
#> 51 18.23 1 83 0 1
#> 197 21.60 1 69 1 0
#> 76.1 19.22 1 54 0 1
#> 23 16.92 1 61 0 0
#> 42 12.43 1 49 0 1
#> 92 22.92 1 47 0 1
#> 197.1 21.60 1 69 1 0
#> 99 21.19 1 38 0 1
#> 49.1 12.19 1 48 1 0
#> 111 17.45 1 47 0 1
#> 93 10.33 1 52 0 1
#> 199 19.81 1 NA 0 1
#> 123 13.00 1 44 1 0
#> 106 16.67 1 49 1 0
#> 66 22.13 1 53 0 0
#> 25 6.32 1 34 1 0
#> 41.1 18.02 1 40 1 0
#> 79.1 16.23 1 54 1 0
#> 51.1 18.23 1 83 0 1
#> 195 11.76 1 NA 1 0
#> 4 17.64 1 NA 0 1
#> 51.2 18.23 1 83 0 1
#> 51.3 18.23 1 83 0 1
#> 125.1 15.65 1 67 1 0
#> 43 12.10 1 61 0 1
#> 197.2 21.60 1 69 1 0
#> 183 9.24 1 67 1 0
#> 89 11.44 1 NA 0 0
#> 180 14.82 1 37 0 0
#> 51.4 18.23 1 83 0 1
#> 133.1 14.65 1 57 0 0
#> 78 23.88 1 43 0 0
#> 36 21.19 1 48 0 1
#> 128 20.35 1 35 0 1
#> 110 17.56 1 65 0 1
#> 134 17.81 1 47 1 0
#> 76.2 19.22 1 54 0 1
#> 110.1 17.56 1 65 0 1
#> 134.1 17.81 1 47 1 0
#> 61.1 10.12 1 36 0 1
#> 184 17.77 1 38 0 0
#> 153 21.33 1 55 1 0
#> 177 12.53 1 75 0 0
#> 43.1 12.10 1 61 0 1
#> 157 15.10 1 47 0 0
#> 181.1 16.46 1 45 0 1
#> 133.2 14.65 1 57 0 0
#> 89.1 11.44 1 NA 0 0
#> 99.1 21.19 1 38 0 1
#> 107 11.18 1 54 1 0
#> 10 10.53 1 34 0 0
#> 179 18.63 1 42 0 0
#> 99.2 21.19 1 38 0 1
#> 169 22.41 1 46 0 0
#> 134.2 17.81 1 47 1 0
#> 49.2 12.19 1 48 1 0
#> 6 15.64 1 39 0 0
#> 153.1 21.33 1 55 1 0
#> 52 10.42 1 52 0 1
#> 18 15.21 1 49 1 0
#> 134.3 17.81 1 47 1 0
#> 139 21.49 1 63 1 0
#> 79.2 16.23 1 54 1 0
#> 55 19.34 1 69 0 1
#> 158 20.14 1 74 1 0
#> 129 23.41 1 53 1 0
#> 155.1 13.08 1 26 0 0
#> 58 19.34 1 39 0 0
#> 171 16.57 1 41 0 1
#> 154 12.63 1 20 1 0
#> 129.1 23.41 1 53 1 0
#> 130.1 16.47 1 53 0 1
#> 158.1 20.14 1 74 1 0
#> 134.4 17.81 1 47 1 0
#> 128.1 20.35 1 35 0 1
#> 117 17.46 1 26 0 1
#> 57.1 14.46 1 45 0 1
#> 128.2 20.35 1 35 0 1
#> 78.1 23.88 1 43 0 0
#> 88 18.37 1 47 0 0
#> 39 15.59 1 37 0 1
#> 90 20.94 1 50 0 1
#> 140 12.68 1 59 1 0
#> 189 10.51 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 90.1 20.94 1 50 0 1
#> 66.1 22.13 1 53 0 0
#> 43.2 12.10 1 61 0 1
#> 91 5.33 1 61 0 1
#> 136 21.83 1 43 0 1
#> 199.1 19.81 1 NA 0 1
#> 100 16.07 1 60 0 0
#> 85 16.44 1 36 0 0
#> 6.1 15.64 1 39 0 0
#> 191 24.00 0 60 0 1
#> 186 24.00 0 45 1 0
#> 112 24.00 0 61 0 0
#> 163 24.00 0 66 0 0
#> 162 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 198 24.00 0 66 0 1
#> 53 24.00 0 32 0 1
#> 115 24.00 0 NA 1 0
#> 72 24.00 0 40 0 1
#> 162.1 24.00 0 51 0 0
#> 82 24.00 0 34 0 0
#> 103 24.00 0 56 1 0
#> 132 24.00 0 55 0 0
#> 185 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 162.2 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 120 24.00 0 68 0 1
#> 119 24.00 0 17 0 0
#> 87 24.00 0 27 0 0
#> 21 24.00 0 47 0 0
#> 9.1 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 82.1 24.00 0 34 0 0
#> 151 24.00 0 42 0 0
#> 84 24.00 0 39 0 1
#> 178 24.00 0 52 1 0
#> 47 24.00 0 38 0 1
#> 102 24.00 0 49 0 0
#> 104 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 17 24.00 0 38 0 1
#> 104.1 24.00 0 50 1 0
#> 144 24.00 0 28 0 1
#> 141 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 198.1 24.00 0 66 0 1
#> 142 24.00 0 53 0 0
#> 120.1 24.00 0 68 0 1
#> 151.1 24.00 0 42 0 0
#> 71 24.00 0 51 0 0
#> 72.1 24.00 0 40 0 1
#> 80 24.00 0 41 0 0
#> 12 24.00 0 63 0 0
#> 176 24.00 0 43 0 1
#> 103.1 24.00 0 56 1 0
#> 126 24.00 0 48 0 0
#> 47.1 24.00 0 38 0 1
#> 161 24.00 0 45 0 0
#> 3 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 137 24.00 0 45 1 0
#> 72.2 24.00 0 40 0 1
#> 176.1 24.00 0 43 0 1
#> 20 24.00 0 46 1 0
#> 65 24.00 0 57 1 0
#> 94 24.00 0 51 0 1
#> 143.1 24.00 0 51 0 0
#> 65.1 24.00 0 57 1 0
#> 185.1 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 83 24.00 0 6 0 0
#> 185.2 24.00 0 44 1 0
#> 83.1 24.00 0 6 0 0
#> 7 24.00 0 37 1 0
#> 121 24.00 0 57 1 0
#> 176.2 24.00 0 43 0 1
#> 7.1 24.00 0 37 1 0
#> 131 24.00 0 66 0 0
#> 161.1 24.00 0 45 0 0
#> 28 24.00 0 67 1 0
#> 119.1 24.00 0 17 0 0
#> 172 24.00 0 41 0 0
#> 44 24.00 0 56 0 0
#> 135 24.00 0 58 1 0
#> 178.1 24.00 0 52 1 0
#> 64 24.00 0 43 0 0
#> 103.2 24.00 0 56 1 0
#> 21.1 24.00 0 47 0 0
#> 115.1 24.00 0 NA 1 0
#> 20.1 24.00 0 46 1 0
#> 28.1 24.00 0 67 1 0
#> 193 24.00 0 45 0 1
#> 9.2 24.00 0 31 1 0
#> 120.2 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.33 NA NA NA
#> 2 age, Cure model 0.0241 NA NA NA
#> 3 grade_ii, Cure model 0.176 NA NA NA
#> 4 grade_iii, Cure model 0.866 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00431 NA NA NA
#> 2 grade_ii, Survival model 0.162 NA NA NA
#> 3 grade_iii, Survival model 0.244 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.32947 0.02414 0.17559 0.86595
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 249.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.32946502 0.02414302 0.17559326 0.86595371
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004314238 0.162456994 0.243604340
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.838349438 0.218610340 0.312282782 0.541564272 0.246507855 0.708106777
#> [7] 0.590139410 0.387693500 0.737882038 0.628984702 0.949339867 0.274904376
#> [13] 0.502396309 0.848483225 0.560972301 0.331625083 0.767885323 0.341300782
#> [19] 0.082535843 0.274904376 0.512154602 0.828243513 0.036551532 0.082535843
#> [25] 0.138381670 0.848483225 0.492635995 0.939172730 0.787898225 0.521956111
#> [31] 0.054743851 0.979684159 0.387693500 0.590139410 0.341300782 0.341300782
#> [37] 0.341300782 0.628984702 0.878569531 0.082535843 0.969525575 0.698132046
#> [43] 0.341300782 0.708106777 0.006226641 0.138381670 0.191934152 0.463473956
#> [49] 0.406972742 0.274904376 0.463473956 0.406972742 0.949339867 0.453688527
#> [55] 0.119219970 0.818133551 0.878569531 0.688178299 0.560972301 0.708106777
#> [61] 0.138381670 0.908675910 0.918832012 0.302676579 0.138381670 0.045481502
#> [67] 0.406972742 0.848483225 0.648611356 0.119219970 0.929003453 0.678250907
#> [73] 0.406972742 0.109342701 0.590139410 0.256043881 0.227965134 0.020752607
#> [79] 0.767885323 0.256043881 0.531766425 0.808058009 0.020752607 0.541564272
#> [85] 0.227965134 0.406972742 0.191934152 0.482867621 0.737882038 0.191934152
#> [91] 0.006226641 0.321927263 0.668330453 0.173459525 0.797972516 0.757840786
#> [97] 0.173459525 0.054743851 0.878569531 0.989841069 0.072889636 0.619130482
#> [103] 0.580346411 0.648611356 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 56 150 8 130 105 133 79 41 57 125 61 76 45
#> 12.21 20.33 18.43 16.47 19.75 14.65 16.23 18.02 14.46 15.65 10.12 19.22 17.42
#> 49 181 108 155 51 197 76.1 23 42 92 197.1 99 49.1
#> 12.19 16.46 18.29 13.08 18.23 21.60 19.22 16.92 12.43 22.92 21.60 21.19 12.19
#> 111 93 123 106 66 25 41.1 79.1 51.1 51.2 51.3 125.1 43
#> 17.45 10.33 13.00 16.67 22.13 6.32 18.02 16.23 18.23 18.23 18.23 15.65 12.10
#> 197.2 183 180 51.4 133.1 78 36 128 110 134 76.2 110.1 134.1
#> 21.60 9.24 14.82 18.23 14.65 23.88 21.19 20.35 17.56 17.81 19.22 17.56 17.81
#> 61.1 184 153 177 43.1 157 181.1 133.2 99.1 107 10 179 99.2
#> 10.12 17.77 21.33 12.53 12.10 15.10 16.46 14.65 21.19 11.18 10.53 18.63 21.19
#> 169 134.2 49.2 6 153.1 52 18 134.3 139 79.2 55 158 129
#> 22.41 17.81 12.19 15.64 21.33 10.42 15.21 17.81 21.49 16.23 19.34 20.14 23.41
#> 155.1 58 171 154 129.1 130.1 158.1 134.4 128.1 117 57.1 128.2 78.1
#> 13.08 19.34 16.57 12.63 23.41 16.47 20.14 17.81 20.35 17.46 14.46 20.35 23.88
#> 88 39 90 140 13 90.1 66.1 43.2 91 136 100 85 6.1
#> 18.37 15.59 20.94 12.68 14.34 20.94 22.13 12.10 5.33 21.83 16.07 16.44 15.64
#> 191 186 112 163 162 19 198 53 72 162.1 82 103 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 9 162.2 62 120 119 87 21 9.1 147 82.1 151 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 47 102 104 143 98 17 104.1 144 141 48 198.1 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 151.1 71 72.1 80 12 176 103.1 126 47.1 161 3 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 137 72.2 176.1 20 65 94 143.1 65.1 185.1 196 83 185.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83.1 7 121 176.2 7.1 131 161.1 28 119.1 172 44 135 178.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 103.2 21.1 20.1 28.1 193 9.2 120.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[50]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005196358 0.503382437 0.385806222
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.14323567 -0.00519571 0.08144029
#> grade_iii, Cure model
#> 1.00769242
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 86 23.81 1 58 0 1
#> 113 22.86 1 34 0 0
#> 45 17.42 1 54 0 1
#> 26 15.77 1 49 0 1
#> 5 16.43 1 51 0 1
#> 92 22.92 1 47 0 1
#> 187 9.92 1 39 1 0
#> 8 18.43 1 32 0 0
#> 153 21.33 1 55 1 0
#> 68 20.62 1 44 0 0
#> 134 17.81 1 47 1 0
#> 164 23.60 1 76 0 1
#> 42 12.43 1 49 0 1
#> 130 16.47 1 53 0 1
#> 85 16.44 1 36 0 0
#> 66 22.13 1 53 0 0
#> 124 9.73 1 NA 1 0
#> 50 10.02 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 32 20.90 1 37 1 0
#> 190 20.81 1 42 1 0
#> 170 19.54 1 43 0 1
#> 16 8.71 1 71 0 1
#> 149 8.37 1 33 1 0
#> 76 19.22 1 54 0 1
#> 157 15.10 1 47 0 0
#> 189 10.51 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 5.1 16.43 1 51 0 1
#> 56 12.21 1 60 0 0
#> 133 14.65 1 57 0 0
#> 43 12.10 1 61 0 1
#> 14 12.89 1 21 0 0
#> 125 15.65 1 67 1 0
#> 61 10.12 1 36 0 1
#> 187.1 9.92 1 39 1 0
#> 24 23.89 1 38 0 0
#> 169 22.41 1 46 0 0
#> 56.1 12.21 1 60 0 0
#> 190.1 20.81 1 42 1 0
#> 10 10.53 1 34 0 0
#> 167 15.55 1 56 1 0
#> 13 14.34 1 54 0 1
#> 159 10.55 1 50 0 1
#> 167.1 15.55 1 56 1 0
#> 101 9.97 1 10 0 1
#> 6 15.64 1 39 0 0
#> 56.2 12.21 1 60 0 0
#> 111 17.45 1 47 0 1
#> 29 15.45 1 68 1 0
#> 56.3 12.21 1 60 0 0
#> 106 16.67 1 49 1 0
#> 89 11.44 1 NA 0 0
#> 58 19.34 1 39 0 0
#> 49 12.19 1 48 1 0
#> 150 20.33 1 48 0 0
#> 154 12.63 1 20 1 0
#> 55 19.34 1 69 0 1
#> 16.1 8.71 1 71 0 1
#> 155 13.08 1 26 0 0
#> 13.1 14.34 1 54 0 1
#> 192 16.44 1 31 1 0
#> 167.2 15.55 1 56 1 0
#> 90 20.94 1 50 0 1
#> 26.1 15.77 1 49 0 1
#> 175 21.91 1 43 0 0
#> 189.1 10.51 1 NA 1 0
#> 18.1 15.21 1 49 1 0
#> 199 19.81 1 NA 0 1
#> 37 12.52 1 57 1 0
#> 145 10.07 1 65 1 0
#> 134.1 17.81 1 47 1 0
#> 4 17.64 1 NA 0 1
#> 164.1 23.60 1 76 0 1
#> 133.1 14.65 1 57 0 0
#> 18.2 15.21 1 49 1 0
#> 89.1 11.44 1 NA 0 0
#> 51 18.23 1 83 0 1
#> 93 10.33 1 52 0 1
#> 55.1 19.34 1 69 0 1
#> 189.2 10.51 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 136 21.83 1 43 0 1
#> 42.1 12.43 1 49 0 1
#> 133.2 14.65 1 57 0 0
#> 133.3 14.65 1 57 0 0
#> 169.1 22.41 1 46 0 0
#> 177 12.53 1 75 0 0
#> 23 16.92 1 61 0 0
#> 195 11.76 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 125.1 15.65 1 67 1 0
#> 88 18.37 1 47 0 0
#> 175.1 21.91 1 43 0 0
#> 125.2 15.65 1 67 1 0
#> 15 22.68 1 48 0 0
#> 129 23.41 1 53 1 0
#> 79 16.23 1 54 1 0
#> 90.1 20.94 1 50 0 1
#> 105 19.75 1 60 0 0
#> 190.2 20.81 1 42 1 0
#> 32.1 20.90 1 37 1 0
#> 168 23.72 1 70 0 0
#> 140.1 12.68 1 59 1 0
#> 23.1 16.92 1 61 0 0
#> 14.1 12.89 1 21 0 0
#> 190.3 20.81 1 42 1 0
#> 96 14.54 1 33 0 1
#> 52 10.42 1 52 0 1
#> 57 14.46 1 45 0 1
#> 57.1 14.46 1 45 0 1
#> 77 7.27 1 67 0 1
#> 75 24.00 0 21 1 0
#> 27 24.00 0 63 1 0
#> 119 24.00 0 17 0 0
#> 156 24.00 0 50 1 0
#> 44 24.00 0 56 0 0
#> 27.1 24.00 0 63 1 0
#> 44.1 24.00 0 56 0 0
#> 143 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 178 24.00 0 52 1 0
#> 94 24.00 0 51 0 1
#> 44.2 24.00 0 56 0 0
#> 95 24.00 0 68 0 1
#> 147 24.00 0 76 1 0
#> 116 24.00 0 58 0 1
#> 20 24.00 0 46 1 0
#> 54 24.00 0 53 1 0
#> 135 24.00 0 58 1 0
#> 46 24.00 0 71 0 0
#> 1 24.00 0 23 1 0
#> 9 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 200 24.00 0 64 0 0
#> 21 24.00 0 47 0 0
#> 75.1 24.00 0 21 1 0
#> 178.1 24.00 0 52 1 0
#> 80 24.00 0 41 0 0
#> 67 24.00 0 25 0 0
#> 19 24.00 0 57 0 1
#> 35 24.00 0 51 0 0
#> 198 24.00 0 66 0 1
#> 73 24.00 0 NA 0 1
#> 94.1 24.00 0 51 0 1
#> 135.1 24.00 0 58 1 0
#> 95.1 24.00 0 68 0 1
#> 174 24.00 0 49 1 0
#> 73.1 24.00 0 NA 0 1
#> 72 24.00 0 40 0 1
#> 47 24.00 0 38 0 1
#> 27.2 24.00 0 63 1 0
#> 163 24.00 0 66 0 0
#> 72.1 24.00 0 40 0 1
#> 54.1 24.00 0 53 1 0
#> 148 24.00 0 61 1 0
#> 95.2 24.00 0 68 0 1
#> 161 24.00 0 45 0 0
#> 62 24.00 0 71 0 0
#> 38 24.00 0 31 1 0
#> 198.1 24.00 0 66 0 1
#> 162 24.00 0 51 0 0
#> 67.1 24.00 0 25 0 0
#> 137 24.00 0 45 1 0
#> 118 24.00 0 44 1 0
#> 102 24.00 0 49 0 0
#> 131 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 135.2 24.00 0 58 1 0
#> 71 24.00 0 51 0 0
#> 54.2 24.00 0 53 1 0
#> 62.1 24.00 0 71 0 0
#> 103 24.00 0 56 1 0
#> 20.1 24.00 0 46 1 0
#> 174.1 24.00 0 49 1 0
#> 200.1 24.00 0 64 0 0
#> 21.1 24.00 0 47 0 0
#> 142 24.00 0 53 0 0
#> 160 24.00 0 31 1 0
#> 62.2 24.00 0 71 0 0
#> 161.1 24.00 0 45 0 0
#> 182 24.00 0 35 0 0
#> 119.1 24.00 0 17 0 0
#> 74 24.00 0 43 0 1
#> 46.1 24.00 0 71 0 0
#> 161.2 24.00 0 45 0 0
#> 35.1 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 28 24.00 0 67 1 0
#> 7 24.00 0 37 1 0
#> 102.1 24.00 0 49 0 0
#> 35.2 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 186 24.00 0 45 1 0
#> 71.1 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 135.3 24.00 0 58 1 0
#> 87 24.00 0 27 0 0
#> 193 24.00 0 45 0 1
#> 109.1 24.00 0 48 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.143 NA NA NA
#> 2 age, Cure model -0.00520 NA NA NA
#> 3 grade_ii, Cure model 0.0814 NA NA NA
#> 4 grade_iii, Cure model 1.01 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00520 NA NA NA
#> 2 grade_ii, Survival model 0.503 NA NA NA
#> 3 grade_iii, Survival model 0.386 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.143236 -0.005196 0.081440 1.007692
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 251.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.14323567 -0.00519571 0.08144029 1.00769242
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005196358 0.503382437 0.385806222
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.022868996 0.085029785 0.414012783 0.512508480 0.483249094 0.074790668
#> [7] 0.944711454 0.343706583 0.172612072 0.263771576 0.374264905 0.044378938
#> [13] 0.804358992 0.453730505 0.463673953 0.127378694 0.607536973 0.205489246
#> [19] 0.226268381 0.294026801 0.963139782 0.981562125 0.333612610 0.635276664
#> [25] 0.012338395 0.483249094 0.822951633 0.644691314 0.869589895 0.738622220
#> [31] 0.531790323 0.916649449 0.944711454 0.003648841 0.106177391 0.822951633
#> [37] 0.226268381 0.888416907 0.569855319 0.710408530 0.879010168 0.569855319
#> [43] 0.935387795 0.560192708 0.822951633 0.404075968 0.598021449 0.822951633
#> [49] 0.443761567 0.304141852 0.860162346 0.273770176 0.776200394 0.304141852
#> [55] 0.963139782 0.729166603 0.710408530 0.463673953 0.569855319 0.183916650
#> [61] 0.512508480 0.138699079 0.607536973 0.794977756 0.926027159 0.374264905
#> [67] 0.044378938 0.644691314 0.607536973 0.364049174 0.907250600 0.304141852
#> [73] 0.394101863 0.161124973 0.804358992 0.644691314 0.644691314 0.106177391
#> [79] 0.785570966 0.423923223 0.757461976 0.531790323 0.353846194 0.138699079
#> [85] 0.531790323 0.095473884 0.064336530 0.502723077 0.183916650 0.283850074
#> [91] 0.226268381 0.205489246 0.033081329 0.757461976 0.423923223 0.738622220
#> [97] 0.226268381 0.682081199 0.897839805 0.691595382 0.691595382 0.990782708
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 86 113 45 26 5 92 187 8 153 68 134 164 42
#> 23.81 22.86 17.42 15.77 16.43 22.92 9.92 18.43 21.33 20.62 17.81 23.60 12.43
#> 130 85 66 18 32 190 170 16 149 76 157 78 5.1
#> 16.47 16.44 22.13 15.21 20.90 20.81 19.54 8.71 8.37 19.22 15.10 23.88 16.43
#> 56 133 43 14 125 61 187.1 24 169 56.1 190.1 10 167
#> 12.21 14.65 12.10 12.89 15.65 10.12 9.92 23.89 22.41 12.21 20.81 10.53 15.55
#> 13 159 167.1 101 6 56.2 111 29 56.3 106 58 49 150
#> 14.34 10.55 15.55 9.97 15.64 12.21 17.45 15.45 12.21 16.67 19.34 12.19 20.33
#> 154 55 16.1 155 13.1 192 167.2 90 26.1 175 18.1 37 145
#> 12.63 19.34 8.71 13.08 14.34 16.44 15.55 20.94 15.77 21.91 15.21 12.52 10.07
#> 134.1 164.1 133.1 18.2 51 93 55.1 117 136 42.1 133.2 133.3 169.1
#> 17.81 23.60 14.65 15.21 18.23 10.33 19.34 17.46 21.83 12.43 14.65 14.65 22.41
#> 177 23 140 125.1 88 175.1 125.2 15 129 79 90.1 105 190.2
#> 12.53 16.92 12.68 15.65 18.37 21.91 15.65 22.68 23.41 16.23 20.94 19.75 20.81
#> 32.1 168 140.1 23.1 14.1 190.3 96 52 57 57.1 77 75 27
#> 20.90 23.72 12.68 16.92 12.89 20.81 14.54 10.42 14.46 14.46 7.27 24.00 24.00
#> 119 156 44 27.1 44.1 143 22 178 94 44.2 95 147 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 54 135 46 1 9 165 200 21 75.1 178.1 80 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 35 198 94.1 135.1 95.1 174 72 47 27.2 163 72.1 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 95.2 161 62 38 198.1 162 67.1 137 118 102 131 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.2 71 54.2 62.1 103 20.1 174.1 200.1 21.1 142 160 62.2 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 119.1 74 46.1 161.2 35.1 132 28 7 102.1 35.2 17 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.1 109 135.3 87 193 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[51]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008444317 0.788193240 0.531832488
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.79069850 0.01356488 -0.05137437
#> grade_iii, Cure model
#> 0.92056023
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 36 21.19 1 48 0 1
#> 155 13.08 1 26 0 0
#> 190 20.81 1 42 1 0
#> 127 3.53 1 62 0 1
#> 136 21.83 1 43 0 1
#> 10 10.53 1 34 0 0
#> 78 23.88 1 43 0 0
#> 130 16.47 1 53 0 1
#> 39 15.59 1 37 0 1
#> 99 21.19 1 38 0 1
#> 124 9.73 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 188 16.16 1 46 0 1
#> 180 14.82 1 37 0 0
#> 106 16.67 1 49 1 0
#> 63 22.77 1 31 1 0
#> 188.1 16.16 1 46 0 1
#> 159 10.55 1 50 0 1
#> 42 12.43 1 49 0 1
#> 42.1 12.43 1 49 0 1
#> 79 16.23 1 54 1 0
#> 52 10.42 1 52 0 1
#> 164 23.60 1 76 0 1
#> 13 14.34 1 54 0 1
#> 5 16.43 1 51 0 1
#> 57 14.46 1 45 0 1
#> 51 18.23 1 83 0 1
#> 45 17.42 1 54 0 1
#> 86 23.81 1 58 0 1
#> 167 15.55 1 56 1 0
#> 133 14.65 1 57 0 0
#> 169.1 22.41 1 46 0 0
#> 32 20.90 1 37 1 0
#> 155.1 13.08 1 26 0 0
#> 167.1 15.55 1 56 1 0
#> 188.2 16.16 1 46 0 1
#> 4 17.64 1 NA 0 1
#> 69 23.23 1 25 0 1
#> 14 12.89 1 21 0 0
#> 45.1 17.42 1 54 0 1
#> 99.1 21.19 1 38 0 1
#> 99.2 21.19 1 38 0 1
#> 130.1 16.47 1 53 0 1
#> 85 16.44 1 36 0 0
#> 101 9.97 1 10 0 1
#> 55 19.34 1 69 0 1
#> 114 13.68 1 NA 0 0
#> 15 22.68 1 48 0 0
#> 60 13.15 1 38 1 0
#> 153 21.33 1 55 1 0
#> 195 11.76 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 36.1 21.19 1 48 0 1
#> 190.1 20.81 1 42 1 0
#> 187 9.92 1 39 1 0
#> 111 17.45 1 47 0 1
#> 41 18.02 1 40 1 0
#> 52.1 10.42 1 52 0 1
#> 189 10.51 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 159.1 10.55 1 50 0 1
#> 43 12.10 1 61 0 1
#> 39.1 15.59 1 37 0 1
#> 18 15.21 1 49 1 0
#> 180.1 14.82 1 37 0 0
#> 111.1 17.45 1 47 0 1
#> 169.2 22.41 1 46 0 0
#> 157 15.10 1 47 0 0
#> 167.2 15.55 1 56 1 0
#> 5.1 16.43 1 51 0 1
#> 26 15.77 1 49 0 1
#> 55.1 19.34 1 69 0 1
#> 66 22.13 1 53 0 0
#> 66.1 22.13 1 53 0 0
#> 149 8.37 1 33 1 0
#> 133.1 14.65 1 57 0 0
#> 105.1 19.75 1 60 0 0
#> 170 19.54 1 43 0 1
#> 189.1 10.51 1 NA 1 0
#> 194.1 22.40 1 38 0 1
#> 188.3 16.16 1 46 0 1
#> 155.2 13.08 1 26 0 0
#> 168 23.72 1 70 0 0
#> 150 20.33 1 48 0 0
#> 101.1 9.97 1 10 0 1
#> 123 13.00 1 44 1 0
#> 45.2 17.42 1 54 0 1
#> 168.1 23.72 1 70 0 0
#> 167.3 15.55 1 56 1 0
#> 127.1 3.53 1 62 0 1
#> 175 21.91 1 43 0 0
#> 77 7.27 1 67 0 1
#> 51.1 18.23 1 83 0 1
#> 78.1 23.88 1 43 0 0
#> 18.1 15.21 1 49 1 0
#> 10.1 10.53 1 34 0 0
#> 140 12.68 1 59 1 0
#> 70 7.38 1 30 1 0
#> 26.1 15.77 1 49 0 1
#> 195.1 11.76 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 55.2 19.34 1 69 0 1
#> 32.1 20.90 1 37 1 0
#> 168.2 23.72 1 70 0 0
#> 97 19.14 1 65 0 1
#> 92.1 22.92 1 47 0 1
#> 127.2 3.53 1 62 0 1
#> 130.2 16.47 1 53 0 1
#> 58 19.34 1 39 0 0
#> 187.1 9.92 1 39 1 0
#> 41.1 18.02 1 40 1 0
#> 128 20.35 1 35 0 1
#> 94 24.00 0 51 0 1
#> 11 24.00 0 42 0 1
#> 47 24.00 0 38 0 1
#> 21 24.00 0 47 0 0
#> 53 24.00 0 32 0 1
#> 65 24.00 0 57 1 0
#> 115 24.00 0 NA 1 0
#> 2 24.00 0 9 0 0
#> 94.1 24.00 0 51 0 1
#> 152 24.00 0 36 0 1
#> 191 24.00 0 60 0 1
#> 163 24.00 0 66 0 0
#> 83 24.00 0 6 0 0
#> 71 24.00 0 51 0 0
#> 173 24.00 0 19 0 1
#> 72 24.00 0 40 0 1
#> 109 24.00 0 48 0 0
#> 7 24.00 0 37 1 0
#> 94.2 24.00 0 51 0 1
#> 35 24.00 0 51 0 0
#> 163.1 24.00 0 66 0 0
#> 143 24.00 0 51 0 0
#> 35.1 24.00 0 51 0 0
#> 2.1 24.00 0 9 0 0
#> 196 24.00 0 19 0 0
#> 151 24.00 0 42 0 0
#> 74 24.00 0 43 0 1
#> 182 24.00 0 35 0 0
#> 46 24.00 0 71 0 0
#> 94.3 24.00 0 51 0 1
#> 152.1 24.00 0 36 0 1
#> 17 24.00 0 38 0 1
#> 193 24.00 0 45 0 1
#> 2.2 24.00 0 9 0 0
#> 20 24.00 0 46 1 0
#> 191.1 24.00 0 60 0 1
#> 121 24.00 0 57 1 0
#> 138 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 162 24.00 0 51 0 0
#> 11.1 24.00 0 42 0 1
#> 67 24.00 0 25 0 0
#> 144 24.00 0 28 0 1
#> 94.4 24.00 0 51 0 1
#> 135 24.00 0 58 1 0
#> 135.1 24.00 0 58 1 0
#> 83.1 24.00 0 6 0 0
#> 65.1 24.00 0 57 1 0
#> 27 24.00 0 63 1 0
#> 148 24.00 0 61 1 0
#> 146 24.00 0 63 1 0
#> 104 24.00 0 50 1 0
#> 120 24.00 0 68 0 1
#> 64 24.00 0 43 0 0
#> 173.1 24.00 0 19 0 1
#> 109.1 24.00 0 48 0 0
#> 121.1 24.00 0 57 1 0
#> 185 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 48 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 163.2 24.00 0 66 0 0
#> 9 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 22 24.00 0 52 1 0
#> 142 24.00 0 53 0 0
#> 176 24.00 0 43 0 1
#> 119 24.00 0 17 0 0
#> 20.1 24.00 0 46 1 0
#> 75 24.00 0 21 1 0
#> 146.1 24.00 0 63 1 0
#> 141 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 64.1 24.00 0 43 0 0
#> 64.2 24.00 0 43 0 0
#> 38 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 176.1 24.00 0 43 0 1
#> 122 24.00 0 66 0 0
#> 34 24.00 0 36 0 0
#> 152.2 24.00 0 36 0 1
#> 103 24.00 0 56 1 0
#> 31 24.00 0 36 0 1
#> 103.1 24.00 0 56 1 0
#> 162.1 24.00 0 51 0 0
#> 186 24.00 0 45 1 0
#> 103.2 24.00 0 56 1 0
#> 71.1 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.791 NA NA NA
#> 2 age, Cure model 0.0136 NA NA NA
#> 3 grade_ii, Cure model -0.0514 NA NA NA
#> 4 grade_iii, Cure model 0.921 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00844 NA NA NA
#> 2 grade_ii, Survival model 0.788 NA NA NA
#> 3 grade_iii, Survival model 0.532 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.79070 0.01356 -0.05137 0.92056
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 252.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.79069850 0.01356488 -0.05137437 0.92056023
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008444317 0.788193240 0.531832488
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.231142989 0.778015466 0.299898366 0.974148323 0.208440947 0.876891287
#> [7] 0.004253762 0.512870070 0.634000516 0.231142989 0.122089268 0.578891091
#> [13] 0.714649682 0.503287967 0.101228506 0.578891091 0.859030539 0.832125435
#> [19] 0.832125435 0.569421594 0.894843298 0.056205624 0.759877489 0.550517252
#> [25] 0.750768050 0.416361282 0.474844280 0.017914159 0.652379052 0.732623827
#> [31] 0.122089268 0.280080778 0.778015466 0.652379052 0.578891091 0.068674392
#> [37] 0.814039671 0.474844280 0.231142989 0.231142989 0.512870070 0.540947252
#> [43] 0.912760398 0.367921370 0.111496108 0.768978332 0.219903868 0.153638280
#> [49] 0.231142989 0.299898366 0.930481249 0.455595873 0.436229391 0.894843298
#> [55] 0.338397200 0.859030539 0.850031474 0.634000516 0.687887876 0.714649682
#> [61] 0.455595873 0.122089268 0.705666404 0.652379052 0.550517252 0.615490395
#> [67] 0.367921370 0.174766758 0.174766758 0.948007758 0.732623827 0.338397200
#> [73] 0.358021497 0.153638280 0.578891091 0.778015466 0.027016297 0.328666320
#> [79] 0.912760398 0.804996435 0.474844280 0.027016297 0.652379052 0.974148323
#> [85] 0.196861173 0.965451802 0.416361282 0.004253762 0.687887876 0.876891287
#> [91] 0.823099263 0.956757895 0.615490395 0.080349280 0.367921370 0.280080778
#> [97] 0.027016297 0.406380868 0.080349280 0.974148323 0.512870070 0.367921370
#> [103] 0.930481249 0.436229391 0.319030524 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 36 155 190 127 136 10 78 130 39 99 169 188 180
#> 21.19 13.08 20.81 3.53 21.83 10.53 23.88 16.47 15.59 21.19 22.41 16.16 14.82
#> 106 63 188.1 159 42 42.1 79 52 164 13 5 57 51
#> 16.67 22.77 16.16 10.55 12.43 12.43 16.23 10.42 23.60 14.34 16.43 14.46 18.23
#> 45 86 167 133 169.1 32 155.1 167.1 188.2 69 14 45.1 99.1
#> 17.42 23.81 15.55 14.65 22.41 20.90 13.08 15.55 16.16 23.23 12.89 17.42 21.19
#> 99.2 130.1 85 101 55 15 60 153 194 36.1 190.1 187 111
#> 21.19 16.47 16.44 9.97 19.34 22.68 13.15 21.33 22.40 21.19 20.81 9.92 17.45
#> 41 52.1 105 159.1 43 39.1 18 180.1 111.1 169.2 157 167.2 5.1
#> 18.02 10.42 19.75 10.55 12.10 15.59 15.21 14.82 17.45 22.41 15.10 15.55 16.43
#> 26 55.1 66 66.1 149 133.1 105.1 170 194.1 188.3 155.2 168 150
#> 15.77 19.34 22.13 22.13 8.37 14.65 19.75 19.54 22.40 16.16 13.08 23.72 20.33
#> 101.1 123 45.2 168.1 167.3 127.1 175 77 51.1 78.1 18.1 10.1 140
#> 9.97 13.00 17.42 23.72 15.55 3.53 21.91 7.27 18.23 23.88 15.21 10.53 12.68
#> 70 26.1 92 55.2 32.1 168.2 97 92.1 127.2 130.2 58 187.1 41.1
#> 7.38 15.77 22.92 19.34 20.90 23.72 19.14 22.92 3.53 16.47 19.34 9.92 18.02
#> 128 94 11 47 21 53 65 2 94.1 152 191 163 83
#> 20.35 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 173 72 109 7 94.2 35 163.1 143 35.1 2.1 196 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 182 46 94.3 152.1 17 193 2.2 20 191.1 121 138 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 11.1 67 144 94.4 135 135.1 83.1 65.1 27 148 146 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 64 173.1 109.1 121.1 185 147 48 160 163.2 9 82 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 176 119 20.1 75 146.1 141 112 64.1 64.2 38 200 176.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 34 152.2 103 31 103.1 162.1 186 103.2 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[52]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004661473 0.878503277 0.471838722
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -3.507316e-01 5.104893e-05 1.590315e-01
#> grade_iii, Cure model
#> 1.144553e+00
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 52 10.42 1 52 0 1
#> 36 21.19 1 48 0 1
#> 93 10.33 1 52 0 1
#> 90 20.94 1 50 0 1
#> 108 18.29 1 39 0 1
#> 69 23.23 1 25 0 1
#> 45 17.42 1 54 0 1
#> 92 22.92 1 47 0 1
#> 45.1 17.42 1 54 0 1
#> 153 21.33 1 55 1 0
#> 10 10.53 1 34 0 0
#> 93.1 10.33 1 52 0 1
#> 164 23.60 1 76 0 1
#> 167 15.55 1 56 1 0
#> 30 17.43 1 78 0 0
#> 8 18.43 1 32 0 0
#> 124 9.73 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 130 16.47 1 53 0 1
#> 184 17.77 1 38 0 0
#> 8.1 18.43 1 32 0 0
#> 195 11.76 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 159 10.55 1 50 0 1
#> 43 12.10 1 61 0 1
#> 106 16.67 1 49 1 0
#> 123 13.00 1 44 1 0
#> 16 8.71 1 71 0 1
#> 23 16.92 1 61 0 0
#> 79 16.23 1 54 1 0
#> 195.1 11.76 1 NA 1 0
#> 52.1 10.42 1 52 0 1
#> 108.1 18.29 1 39 0 1
#> 179 18.63 1 42 0 0
#> 90.1 20.94 1 50 0 1
#> 108.2 18.29 1 39 0 1
#> 190 20.81 1 42 1 0
#> 15 22.68 1 48 0 0
#> 99 21.19 1 38 0 1
#> 45.2 17.42 1 54 0 1
#> 134 17.81 1 47 1 0
#> 51 18.23 1 83 0 1
#> 43.1 12.10 1 61 0 1
#> 167.1 15.55 1 56 1 0
#> 105 19.75 1 60 0 0
#> 60 13.15 1 38 1 0
#> 166 19.98 1 48 0 0
#> 37 12.52 1 57 1 0
#> 107 11.18 1 54 1 0
#> 89 11.44 1 NA 0 0
#> 55 19.34 1 69 0 1
#> 59 10.16 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 25 6.32 1 34 1 0
#> 188 16.16 1 46 0 1
#> 136 21.83 1 43 0 1
#> 168 23.72 1 70 0 0
#> 5 16.43 1 51 0 1
#> 59.1 10.16 1 NA 1 0
#> 36.1 21.19 1 48 0 1
#> 199 19.81 1 NA 0 1
#> 89.1 11.44 1 NA 0 0
#> 169 22.41 1 46 0 0
#> 32 20.90 1 37 1 0
#> 36.2 21.19 1 48 0 1
#> 70 7.38 1 30 1 0
#> 106.1 16.67 1 49 1 0
#> 70.1 7.38 1 30 1 0
#> 40 18.00 1 28 1 0
#> 111 17.45 1 47 0 1
#> 199.1 19.81 1 NA 0 1
#> 86 23.81 1 58 0 1
#> 91 5.33 1 61 0 1
#> 159.1 10.55 1 50 0 1
#> 23.1 16.92 1 61 0 0
#> 68 20.62 1 44 0 0
#> 66 22.13 1 53 0 0
#> 26 15.77 1 49 0 1
#> 59.2 10.16 1 NA 1 0
#> 61.1 10.12 1 36 0 1
#> 92.1 22.92 1 47 0 1
#> 108.3 18.29 1 39 0 1
#> 117 17.46 1 26 0 1
#> 158 20.14 1 74 1 0
#> 63 22.77 1 31 1 0
#> 106.2 16.67 1 49 1 0
#> 125 15.65 1 67 1 0
#> 10.1 10.53 1 34 0 0
#> 117.1 17.46 1 26 0 1
#> 50 10.02 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 175 21.91 1 43 0 0
#> 78 23.88 1 43 0 0
#> 188.1 16.16 1 46 0 1
#> 117.2 17.46 1 26 0 1
#> 5.1 16.43 1 51 0 1
#> 43.2 12.10 1 61 0 1
#> 175.1 21.91 1 43 0 0
#> 6 15.64 1 39 0 0
#> 101 9.97 1 10 0 1
#> 56 12.21 1 60 0 0
#> 5.2 16.43 1 51 0 1
#> 168.1 23.72 1 70 0 0
#> 56.1 12.21 1 60 0 0
#> 105.1 19.75 1 60 0 0
#> 149.1 8.37 1 33 1 0
#> 97 19.14 1 65 0 1
#> 50.1 10.02 1 NA 1 0
#> 97.1 19.14 1 65 0 1
#> 107.1 11.18 1 54 1 0
#> 43.3 12.10 1 61 0 1
#> 114 13.68 1 NA 0 0
#> 31 24.00 0 36 0 1
#> 146 24.00 0 63 1 0
#> 20 24.00 0 46 1 0
#> 54 24.00 0 53 1 0
#> 7 24.00 0 37 1 0
#> 156 24.00 0 50 1 0
#> 48 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 19 24.00 0 57 0 1
#> 138 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 174 24.00 0 49 1 0
#> 191.1 24.00 0 60 0 1
#> 138.1 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 102 24.00 0 49 0 0
#> 185 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 2 24.00 0 9 0 0
#> 80 24.00 0 41 0 0
#> 120 24.00 0 68 0 1
#> 94 24.00 0 51 0 1
#> 152 24.00 0 36 0 1
#> 28 24.00 0 67 1 0
#> 176 24.00 0 43 0 1
#> 131 24.00 0 66 0 0
#> 122 24.00 0 66 0 0
#> 135 24.00 0 58 1 0
#> 73 24.00 0 NA 0 1
#> 103 24.00 0 56 1 0
#> 80.1 24.00 0 41 0 0
#> 44 24.00 0 56 0 0
#> 67 24.00 0 25 0 0
#> 120.1 24.00 0 68 0 1
#> 87 24.00 0 27 0 0
#> 163 24.00 0 66 0 0
#> 74 24.00 0 43 0 1
#> 120.2 24.00 0 68 0 1
#> 104 24.00 0 50 1 0
#> 173 24.00 0 19 0 1
#> 131.1 24.00 0 66 0 0
#> 103.1 24.00 0 56 1 0
#> 143 24.00 0 51 0 0
#> 67.1 24.00 0 25 0 0
#> 148 24.00 0 61 1 0
#> 74.1 24.00 0 43 0 1
#> 161 24.00 0 45 0 0
#> 172 24.00 0 41 0 0
#> 62 24.00 0 71 0 0
#> 72 24.00 0 40 0 1
#> 143.1 24.00 0 51 0 0
#> 82 24.00 0 34 0 0
#> 198 24.00 0 66 0 1
#> 176.1 24.00 0 43 0 1
#> 21 24.00 0 47 0 0
#> 142 24.00 0 53 0 0
#> 47 24.00 0 38 0 1
#> 83 24.00 0 6 0 0
#> 119 24.00 0 17 0 0
#> 172.1 24.00 0 41 0 0
#> 185.1 24.00 0 44 1 0
#> 147.1 24.00 0 76 1 0
#> 21.1 24.00 0 47 0 0
#> 98 24.00 0 34 1 0
#> 147.2 24.00 0 76 1 0
#> 142.1 24.00 0 53 0 0
#> 122.1 24.00 0 66 0 0
#> 176.2 24.00 0 43 0 1
#> 121 24.00 0 57 1 0
#> 112 24.00 0 61 0 0
#> 162 24.00 0 51 0 0
#> 71 24.00 0 51 0 0
#> 152.1 24.00 0 36 0 1
#> 48.1 24.00 0 31 1 0
#> 120.3 24.00 0 68 0 1
#> 7.1 24.00 0 37 1 0
#> 80.2 24.00 0 41 0 0
#> 132 24.00 0 55 0 0
#> 11 24.00 0 42 0 1
#> 182 24.00 0 35 0 0
#> 115 24.00 0 NA 1 0
#> 131.2 24.00 0 66 0 0
#> 120.4 24.00 0 68 0 1
#> 186.1 24.00 0 45 1 0
#> 34 24.00 0 36 0 0
#> 48.2 24.00 0 31 1 0
#> 20.1 24.00 0 46 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.351 NA NA NA
#> 2 age, Cure model 0.0000510 NA NA NA
#> 3 grade_ii, Cure model 0.159 NA NA NA
#> 4 grade_iii, Cure model 1.14 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00466 NA NA NA
#> 2 grade_ii, Survival model 0.879 NA NA NA
#> 3 grade_iii, Survival model 0.472 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -3.507e-01 5.105e-05 1.590e-01 1.145e+00
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.6
#> Residual Deviance: 243.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -3.507316e-01 5.104893e-05 1.590315e-01 1.144553e+00
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004661473 0.878503277 0.471838722
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.88986173 0.23446129 0.90597588 0.27882729 0.45015348 0.08709355
#> [7] 0.57763652 0.10278633 0.57763652 0.22171766 0.87367198 0.90597588
#> [13] 0.07010819 0.74101015 0.56799417 0.42914353 0.95388664 0.65197647
#> [19] 0.52010102 0.42914353 0.37650777 0.85752609 0.80861013 0.62477538
#> [25] 0.77522686 0.94592764 0.60574291 0.68796150 0.88986173 0.45015348
#> [31] 0.41857941 0.27882729 0.45015348 0.31256932 0.14236755 0.23446129
#> [37] 0.57763652 0.51025548 0.48997449 0.80861013 0.74101015 0.35527597
#> [43] 0.76673533 0.34465399 0.78362995 0.84129781 0.38718252 0.92201645
#> [49] 0.98477016 0.69691798 0.20830945 0.03949245 0.66114002 0.23446129
#> [55] 0.15530841 0.30146538 0.23446129 0.96946281 0.62477538 0.96946281
#> [61] 0.50022933 0.55840146 0.02419850 0.99239110 0.85752609 0.60574291
#> [67] 0.32330004 0.16846132 0.71458340 0.92201645 0.10278633 0.45015348
#> [73] 0.52997691 0.33409725 0.12965890 0.62477538 0.72344103 0.87367198
#> [79] 0.52997691 0.75814712 0.18184336 0.00713025 0.69691798 0.52997691
#> [85] 0.66114002 0.80861013 0.18184336 0.73221683 0.93795850 0.79195753
#> [91] 0.66114002 0.03949245 0.79195753 0.35527597 0.95388664 0.39780982
#> [97] 0.39780982 0.84129781 0.80861013 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 52 36 93 90 108 69 45 92 45.1 153 10 93.1 164
#> 10.42 21.19 10.33 20.94 18.29 23.23 17.42 22.92 17.42 21.33 10.53 10.33 23.60
#> 167 30 8 149 130 184 8.1 170 159 43 106 123 16
#> 15.55 17.43 18.43 8.37 16.47 17.77 18.43 19.54 10.55 12.10 16.67 13.00 8.71
#> 23 79 52.1 108.1 179 90.1 108.2 190 15 99 45.2 134 51
#> 16.92 16.23 10.42 18.29 18.63 20.94 18.29 20.81 22.68 21.19 17.42 17.81 18.23
#> 43.1 167.1 105 60 166 37 107 55 61 25 188 136 168
#> 12.10 15.55 19.75 13.15 19.98 12.52 11.18 19.34 10.12 6.32 16.16 21.83 23.72
#> 5 36.1 169 32 36.2 70 106.1 70.1 40 111 86 91 159.1
#> 16.43 21.19 22.41 20.90 21.19 7.38 16.67 7.38 18.00 17.45 23.81 5.33 10.55
#> 23.1 68 66 26 61.1 92.1 108.3 117 158 63 106.2 125 10.1
#> 16.92 20.62 22.13 15.77 10.12 22.92 18.29 17.46 20.14 22.77 16.67 15.65 10.53
#> 117.1 57 175 78 188.1 117.2 5.1 43.2 175.1 6 101 56 5.2
#> 17.46 14.46 21.91 23.88 16.16 17.46 16.43 12.10 21.91 15.64 9.97 12.21 16.43
#> 168.1 56.1 105.1 149.1 97 97.1 107.1 43.3 31 146 20 54 7
#> 23.72 12.21 19.75 8.37 19.14 19.14 11.18 12.10 24.00 24.00 24.00 24.00 24.00
#> 156 48 191 19 138 118 186 174 191.1 138.1 84 102 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 2 80 120 94 152 28 176 131 122 135 103 80.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 67 120.1 87 163 74 120.2 104 173 131.1 103.1 143 67.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 74.1 161 172 62 72 143.1 82 198 176.1 21 142 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 119 172.1 185.1 147.1 21.1 98 147.2 142.1 122.1 176.2 121 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 71 152.1 48.1 120.3 7.1 80.2 132 11 182 131.2 120.4 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 48.2 20.1
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[53]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00588165 0.93012306 0.72986879
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.45634403 0.02549202 0.30994399
#> grade_iii, Cure model
#> 0.99375583
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 42 12.43 1 49 0 1
#> 61 10.12 1 36 0 1
#> 99 21.19 1 38 0 1
#> 99.1 21.19 1 38 0 1
#> 92 22.92 1 47 0 1
#> 30 17.43 1 78 0 0
#> 29 15.45 1 68 1 0
#> 13 14.34 1 54 0 1
#> 158 20.14 1 74 1 0
#> 29.1 15.45 1 68 1 0
#> 91 5.33 1 61 0 1
#> 150 20.33 1 48 0 0
#> 127 3.53 1 62 0 1
#> 192 16.44 1 31 1 0
#> 179 18.63 1 42 0 0
#> 60 13.15 1 38 1 0
#> 14 12.89 1 21 0 0
#> 56 12.21 1 60 0 0
#> 110 17.56 1 65 0 1
#> 106 16.67 1 49 1 0
#> 32 20.90 1 37 1 0
#> 6 15.64 1 39 0 0
#> 45 17.42 1 54 0 1
#> 197 21.60 1 69 1 0
#> 167 15.55 1 56 1 0
#> 127.1 3.53 1 62 0 1
#> 167.1 15.55 1 56 1 0
#> 90 20.94 1 50 0 1
#> 56.1 12.21 1 60 0 0
#> 5 16.43 1 51 0 1
#> 59 10.16 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 145 10.07 1 65 1 0
#> 18 15.21 1 49 1 0
#> 183 9.24 1 67 1 0
#> 10 10.53 1 34 0 0
#> 194 22.40 1 38 0 1
#> 61.1 10.12 1 36 0 1
#> 29.2 15.45 1 68 1 0
#> 168 23.72 1 70 0 0
#> 51 18.23 1 83 0 1
#> 29.3 15.45 1 68 1 0
#> 111.1 17.45 1 47 0 1
#> 97 19.14 1 65 0 1
#> 91.1 5.33 1 61 0 1
#> 96 14.54 1 33 0 1
#> 183.1 9.24 1 67 1 0
#> 158.1 20.14 1 74 1 0
#> 66 22.13 1 53 0 0
#> 13.1 14.34 1 54 0 1
#> 16 8.71 1 71 0 1
#> 91.2 5.33 1 61 0 1
#> 105 19.75 1 60 0 0
#> 68 20.62 1 44 0 0
#> 127.2 3.53 1 62 0 1
#> 111.2 17.45 1 47 0 1
#> 18.1 15.21 1 49 1 0
#> 77 7.27 1 67 0 1
#> 168.1 23.72 1 70 0 0
#> 181 16.46 1 45 0 1
#> 36 21.19 1 48 0 1
#> 169 22.41 1 46 0 0
#> 187 9.92 1 39 1 0
#> 168.2 23.72 1 70 0 0
#> 63 22.77 1 31 1 0
#> 78 23.88 1 43 0 0
#> 51.1 18.23 1 83 0 1
#> 123 13.00 1 44 1 0
#> 166 19.98 1 48 0 0
#> 18.2 15.21 1 49 1 0
#> 70 7.38 1 30 1 0
#> 140 12.68 1 59 1 0
#> 167.2 15.55 1 56 1 0
#> 192.1 16.44 1 31 1 0
#> 25 6.32 1 34 1 0
#> 133 14.65 1 57 0 0
#> 125 15.65 1 67 1 0
#> 5.1 16.43 1 51 0 1
#> 181.1 16.46 1 45 0 1
#> 63.1 22.77 1 31 1 0
#> 179.1 18.63 1 42 0 0
#> 164 23.60 1 76 0 1
#> 39 15.59 1 37 0 1
#> 85 16.44 1 36 0 0
#> 129 23.41 1 53 1 0
#> 149 8.37 1 33 1 0
#> 114 13.68 1 NA 0 0
#> 8 18.43 1 32 0 0
#> 90.1 20.94 1 50 0 1
#> 168.3 23.72 1 70 0 0
#> 100 16.07 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 187.1 9.92 1 39 1 0
#> 157 15.10 1 47 0 0
#> 60.1 13.15 1 38 1 0
#> 187.2 9.92 1 39 1 0
#> 43 12.10 1 61 0 1
#> 29.4 15.45 1 68 1 0
#> 164.1 23.60 1 76 0 1
#> 36.1 21.19 1 48 0 1
#> 154 12.63 1 20 1 0
#> 13.2 14.34 1 54 0 1
#> 49 12.19 1 48 1 0
#> 187.3 9.92 1 39 1 0
#> 57 14.46 1 45 0 1
#> 23 16.92 1 61 0 0
#> 139 21.49 1 63 1 0
#> 169.1 22.41 1 46 0 0
#> 78.1 23.88 1 43 0 0
#> 32.1 20.90 1 37 1 0
#> 90.2 20.94 1 50 0 1
#> 43.1 12.10 1 61 0 1
#> 44 24.00 0 56 0 0
#> 62 24.00 0 71 0 0
#> 172 24.00 0 41 0 0
#> 7 24.00 0 37 1 0
#> 11 24.00 0 42 0 1
#> 7.1 24.00 0 37 1 0
#> 28 24.00 0 67 1 0
#> 80 24.00 0 41 0 0
#> 102 24.00 0 49 0 0
#> 53 24.00 0 32 0 1
#> 20 24.00 0 46 1 0
#> 200 24.00 0 64 0 0
#> 196 24.00 0 19 0 0
#> 200.1 24.00 0 64 0 0
#> 132 24.00 0 55 0 0
#> 47 24.00 0 38 0 1
#> 144 24.00 0 28 0 1
#> 122 24.00 0 66 0 0
#> 137 24.00 0 45 1 0
#> 137.1 24.00 0 45 1 0
#> 95 24.00 0 68 0 1
#> 115 24.00 0 NA 1 0
#> 156 24.00 0 50 1 0
#> 87 24.00 0 27 0 0
#> 80.1 24.00 0 41 0 0
#> 95.1 24.00 0 68 0 1
#> 62.1 24.00 0 71 0 0
#> 148 24.00 0 61 1 0
#> 144.1 24.00 0 28 0 1
#> 200.2 24.00 0 64 0 0
#> 118 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 144.2 24.00 0 28 0 1
#> 161 24.00 0 45 0 0
#> 20.1 24.00 0 46 1 0
#> 28.1 24.00 0 67 1 0
#> 152 24.00 0 36 0 1
#> 200.3 24.00 0 64 0 0
#> 33 24.00 0 53 0 0
#> 200.4 24.00 0 64 0 0
#> 138 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 185 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 17 24.00 0 38 0 1
#> 156.1 24.00 0 50 1 0
#> 7.2 24.00 0 37 1 0
#> 138.1 24.00 0 44 1 0
#> 47.1 24.00 0 38 0 1
#> 12 24.00 0 63 0 0
#> 151 24.00 0 42 0 0
#> 20.2 24.00 0 46 1 0
#> 31 24.00 0 36 0 1
#> 186 24.00 0 45 1 0
#> 65 24.00 0 57 1 0
#> 27 24.00 0 63 1 0
#> 126.1 24.00 0 48 0 0
#> 174 24.00 0 49 1 0
#> 185.1 24.00 0 44 1 0
#> 122.1 24.00 0 66 0 0
#> 151.1 24.00 0 42 0 0
#> 156.2 24.00 0 50 1 0
#> 138.2 24.00 0 44 1 0
#> 172.1 24.00 0 41 0 0
#> 144.3 24.00 0 28 0 1
#> 156.3 24.00 0 50 1 0
#> 176 24.00 0 43 0 1
#> 174.1 24.00 0 49 1 0
#> 147 24.00 0 76 1 0
#> 7.3 24.00 0 37 1 0
#> 162 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 138.3 24.00 0 44 1 0
#> 116 24.00 0 58 0 1
#> 178 24.00 0 52 1 0
#> 176.1 24.00 0 43 0 1
#> 28.2 24.00 0 67 1 0
#> 178.1 24.00 0 52 1 0
#> 83 24.00 0 6 0 0
#> 95.2 24.00 0 68 0 1
#> 31.1 24.00 0 36 0 1
#> 138.4 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 182.1 24.00 0 35 0 0
#> 9 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 47.2 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.46 NA NA NA
#> 2 age, Cure model 0.0255 NA NA NA
#> 3 grade_ii, Cure model 0.310 NA NA NA
#> 4 grade_iii, Cure model 0.994 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00588 NA NA NA
#> 2 grade_ii, Survival model 0.930 NA NA NA
#> 3 grade_iii, Survival model 0.730 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.45634 0.02549 0.30994 0.99376
#>
#> Degrees of Freedom: 195 Total (i.e. Null); 192 Residual
#> Null Deviance: 269.2
#> Residual Deviance: 256.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.45634403 0.02549202 0.30994399 0.99375583
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00588165 0.93012306 0.72986879
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.82209282 0.87073924 0.27265733 0.27265733 0.15481952 0.51375902
#> [7] 0.66736762 0.75753924 0.38257070 0.66736762 0.96257368 0.37277630
#> [13] 0.98136548 0.56776832 0.42994512 0.77935480 0.80083000 0.82907965
#> [19] 0.47741839 0.54120586 0.34395777 0.62669610 0.52294663 0.24783904
#> [25] 0.64344029 0.98136548 0.64344029 0.31402806 0.82907965 0.59309423
#> [31] 0.48685995 0.88439182 0.70520701 0.91734999 0.86381195 0.22185135
#> [37] 0.87073924 0.66736762 0.03981092 0.45856861 0.66736762 0.48685995
#> [43] 0.42043575 0.96257368 0.74258838 0.91734999 0.38257070 0.23474882
#> [49] 0.75753924 0.93038373 0.96257368 0.41083614 0.36304481 0.98136548
#> [55] 0.48685995 0.70520701 0.94980524 0.03981092 0.55022184 0.27265733
#> [61] 0.19583990 0.89120614 0.03981092 0.17062595 0.01098326 0.45856861
#> [67] 0.79369114 0.40130279 0.70520701 0.94338080 0.80797627 0.64344029
#> [73] 0.56776832 0.95621238 0.73503685 0.61831016 0.59309423 0.55022184
#> [79] 0.17062595 0.42994512 0.10311183 0.63510511 0.56776832 0.13803234
#> [85] 0.93690678 0.44893549 0.31402806 0.03981092 0.60984278 0.89120614
#> [91] 0.72750736 0.77935480 0.89120614 0.85003288 0.66736762 0.10311183
#> [97] 0.27265733 0.81507285 0.75753924 0.84306424 0.89120614 0.75008587
#> [103] 0.53205263 0.26046969 0.19583990 0.01098326 0.34395777 0.31402806
#> [109] 0.85003288 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 42 61 99 99.1 92 30 29 13 158 29.1 91 150 127
#> 12.43 10.12 21.19 21.19 22.92 17.43 15.45 14.34 20.14 15.45 5.33 20.33 3.53
#> 192 179 60 14 56 110 106 32 6 45 197 167 127.1
#> 16.44 18.63 13.15 12.89 12.21 17.56 16.67 20.90 15.64 17.42 21.60 15.55 3.53
#> 167.1 90 56.1 5 111 145 18 183 10 194 61.1 29.2 168
#> 15.55 20.94 12.21 16.43 17.45 10.07 15.21 9.24 10.53 22.40 10.12 15.45 23.72
#> 51 29.3 111.1 97 91.1 96 183.1 158.1 66 13.1 16 91.2 105
#> 18.23 15.45 17.45 19.14 5.33 14.54 9.24 20.14 22.13 14.34 8.71 5.33 19.75
#> 68 127.2 111.2 18.1 77 168.1 181 36 169 187 168.2 63 78
#> 20.62 3.53 17.45 15.21 7.27 23.72 16.46 21.19 22.41 9.92 23.72 22.77 23.88
#> 51.1 123 166 18.2 70 140 167.2 192.1 25 133 125 5.1 181.1
#> 18.23 13.00 19.98 15.21 7.38 12.68 15.55 16.44 6.32 14.65 15.65 16.43 16.46
#> 63.1 179.1 164 39 85 129 149 8 90.1 168.3 100 187.1 157
#> 22.77 18.63 23.60 15.59 16.44 23.41 8.37 18.43 20.94 23.72 16.07 9.92 15.10
#> 60.1 187.2 43 29.4 164.1 36.1 154 13.2 49 187.3 57 23 139
#> 13.15 9.92 12.10 15.45 23.60 21.19 12.63 14.34 12.19 9.92 14.46 16.92 21.49
#> 169.1 78.1 32.1 90.2 43.1 44 62 172 7 11 7.1 28 80
#> 22.41 23.88 20.90 20.94 12.10 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 53 20 200 196 200.1 132 47 144 122 137 137.1 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 87 80.1 95.1 62.1 148 144.1 200.2 118 75 144.2 161 20.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28.1 152 200.3 33 200.4 138 126 185 182 17 156.1 7.2 138.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.1 12 151 20.2 31 186 65 27 126.1 174 185.1 122.1 151.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.2 138.2 172.1 144.3 156.3 176 174.1 147 7.3 162 21 138.3 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 176.1 28.2 178.1 83 95.2 31.1 138.4 143 182.1 9 71 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.2
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[54]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003032669 0.239956054 0.107645164
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.95199410 0.03681101 0.28142665
#> grade_iii, Cure model
#> 0.68423504
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 60 13.15 1 38 1 0
#> 164 23.60 1 76 0 1
#> 123 13.00 1 44 1 0
#> 86 23.81 1 58 0 1
#> 187 9.92 1 39 1 0
#> 56 12.21 1 60 0 0
#> 110 17.56 1 65 0 1
#> 159 10.55 1 50 0 1
#> 56.1 12.21 1 60 0 0
#> 30 17.43 1 78 0 0
#> 36 21.19 1 48 0 1
#> 43 12.10 1 61 0 1
#> 111 17.45 1 47 0 1
#> 41 18.02 1 40 1 0
#> 155 13.08 1 26 0 0
#> 150 20.33 1 48 0 0
#> 100 16.07 1 60 0 0
#> 10 10.53 1 34 0 0
#> 106 16.67 1 49 1 0
#> 85 16.44 1 36 0 0
#> 153 21.33 1 55 1 0
#> 58 19.34 1 39 0 0
#> 29 15.45 1 68 1 0
#> 96 14.54 1 33 0 1
#> 40 18.00 1 28 1 0
#> 158 20.14 1 74 1 0
#> 199 19.81 1 NA 0 1
#> 177 12.53 1 75 0 0
#> 88 18.37 1 47 0 0
#> 68 20.62 1 44 0 0
#> 89 11.44 1 NA 0 0
#> 86.1 23.81 1 58 0 1
#> 52 10.42 1 52 0 1
#> 50 10.02 1 NA 1 0
#> 100.1 16.07 1 60 0 0
#> 6 15.64 1 39 0 0
#> 13 14.34 1 54 0 1
#> 167 15.55 1 56 1 0
#> 13.1 14.34 1 54 0 1
#> 23 16.92 1 61 0 0
#> 39 15.59 1 37 0 1
#> 168 23.72 1 70 0 0
#> 168.1 23.72 1 70 0 0
#> 139 21.49 1 63 1 0
#> 183 9.24 1 67 1 0
#> 171 16.57 1 41 0 1
#> 183.1 9.24 1 67 1 0
#> 150.1 20.33 1 48 0 0
#> 60.1 13.15 1 38 1 0
#> 55 19.34 1 69 0 1
#> 50.1 10.02 1 NA 1 0
#> 177.1 12.53 1 75 0 0
#> 181 16.46 1 45 0 1
#> 79 16.23 1 54 1 0
#> 124 9.73 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 145 10.07 1 65 1 0
#> 114 13.68 1 NA 0 0
#> 29.1 15.45 1 68 1 0
#> 129 23.41 1 53 1 0
#> 177.2 12.53 1 75 0 0
#> 153.1 21.33 1 55 1 0
#> 101 9.97 1 10 0 1
#> 190 20.81 1 42 1 0
#> 49 12.19 1 48 1 0
#> 199.1 19.81 1 NA 0 1
#> 125 15.65 1 67 1 0
#> 100.2 16.07 1 60 0 0
#> 171.1 16.57 1 41 0 1
#> 183.2 9.24 1 67 1 0
#> 50.2 10.02 1 NA 1 0
#> 157 15.10 1 47 0 0
#> 13.2 14.34 1 54 0 1
#> 157.1 15.10 1 47 0 0
#> 76 19.22 1 54 0 1
#> 6.1 15.64 1 39 0 0
#> 91 5.33 1 61 0 1
#> 179 18.63 1 42 0 0
#> 113 22.86 1 34 0 0
#> 16 8.71 1 71 0 1
#> 45 17.42 1 54 0 1
#> 140 12.68 1 59 1 0
#> 63 22.77 1 31 1 0
#> 4 17.64 1 NA 0 1
#> 29.2 15.45 1 68 1 0
#> 13.3 14.34 1 54 0 1
#> 127 3.53 1 62 0 1
#> 50.3 10.02 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 76.1 19.22 1 54 0 1
#> 197 21.60 1 69 1 0
#> 107 11.18 1 54 1 0
#> 30.1 17.43 1 78 0 0
#> 76.2 19.22 1 54 0 1
#> 184 17.77 1 38 0 0
#> 43.1 12.10 1 61 0 1
#> 175 21.91 1 43 0 0
#> 78 23.88 1 43 0 0
#> 127.1 3.53 1 62 0 1
#> 40.1 18.00 1 28 1 0
#> 40.2 18.00 1 28 1 0
#> 100.3 16.07 1 60 0 0
#> 177.3 12.53 1 75 0 0
#> 189 10.51 1 NA 1 0
#> 139.1 21.49 1 63 1 0
#> 90 20.94 1 50 0 1
#> 70 7.38 1 30 1 0
#> 43.2 12.10 1 61 0 1
#> 13.4 14.34 1 54 0 1
#> 164.1 23.60 1 76 0 1
#> 140.1 12.68 1 59 1 0
#> 180 14.82 1 37 0 0
#> 75 24.00 0 21 1 0
#> 44 24.00 0 56 0 0
#> 141 24.00 0 44 1 0
#> 102 24.00 0 49 0 0
#> 178 24.00 0 52 1 0
#> 44.1 24.00 0 56 0 0
#> 200 24.00 0 64 0 0
#> 162 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 141.1 24.00 0 44 1 0
#> 172 24.00 0 41 0 0
#> 67 24.00 0 25 0 0
#> 152 24.00 0 36 0 1
#> 53 24.00 0 32 0 1
#> 116 24.00 0 58 0 1
#> 137 24.00 0 45 1 0
#> 138 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 20 24.00 0 46 1 0
#> 74 24.00 0 43 0 1
#> 185 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 21 24.00 0 47 0 0
#> 48 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 72 24.00 0 40 0 1
#> 103 24.00 0 56 1 0
#> 122 24.00 0 66 0 0
#> 186 24.00 0 45 1 0
#> 94 24.00 0 51 0 1
#> 196 24.00 0 19 0 0
#> 34 24.00 0 36 0 0
#> 200.1 24.00 0 64 0 0
#> 138.1 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 2 24.00 0 9 0 0
#> 46 24.00 0 71 0 0
#> 103.1 24.00 0 56 1 0
#> 172.1 24.00 0 41 0 0
#> 7.1 24.00 0 37 1 0
#> 162.1 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 186.1 24.00 0 45 1 0
#> 120 24.00 0 68 0 1
#> 103.2 24.00 0 56 1 0
#> 35 24.00 0 51 0 0
#> 82 24.00 0 34 0 0
#> 165 24.00 0 47 0 0
#> 71 24.00 0 51 0 0
#> 67.1 24.00 0 25 0 0
#> 161 24.00 0 45 0 0
#> 17 24.00 0 38 0 1
#> 27 24.00 0 63 1 0
#> 53.1 24.00 0 32 0 1
#> 151 24.00 0 42 0 0
#> 87 24.00 0 27 0 0
#> 162.2 24.00 0 51 0 0
#> 72.1 24.00 0 40 0 1
#> 160 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 160.1 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 182 24.00 0 35 0 0
#> 19 24.00 0 57 0 1
#> 19.1 24.00 0 57 0 1
#> 147 24.00 0 76 1 0
#> 121 24.00 0 57 1 0
#> 173 24.00 0 19 0 1
#> 191 24.00 0 60 0 1
#> 62 24.00 0 71 0 0
#> 87.1 24.00 0 27 0 0
#> 172.2 24.00 0 41 0 0
#> 44.2 24.00 0 56 0 0
#> 174 24.00 0 49 1 0
#> 94.1 24.00 0 51 0 1
#> 126 24.00 0 48 0 0
#> 193 24.00 0 45 0 1
#> 17.1 24.00 0 38 0 1
#> 160.2 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 21.1 24.00 0 47 0 0
#> 146 24.00 0 63 1 0
#> 165.1 24.00 0 47 0 0
#> 112 24.00 0 61 0 0
#> 44.3 24.00 0 56 0 0
#> 1.1 24.00 0 23 1 0
#> 73.1 24.00 0 NA 0 1
#> 73.2 24.00 0 NA 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.95 NA NA NA
#> 2 age, Cure model 0.0368 NA NA NA
#> 3 grade_ii, Cure model 0.281 NA NA NA
#> 4 grade_iii, Cure model 0.684 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00303 NA NA NA
#> 2 grade_ii, Survival model 0.240 NA NA NA
#> 3 grade_iii, Survival model 0.108 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.95199 0.03681 0.28143 0.68424
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.2
#> Residual Deviance: 240.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.95199410 0.03681101 0.28142665 0.68423504
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003032669 0.239956054 0.107645164
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.682075325 0.048266442 0.712632004 0.014731338 0.907399994 0.783564530
#> [7] 0.350811500 0.855550692 0.783564530 0.370656583 0.165024466 0.814479582
#> [13] 0.360729354 0.302127503 0.702389221 0.204167461 0.470835908 0.865911276
#> [19] 0.410603986 0.450655014 0.146078631 0.233466254 0.561359988 0.621972802
#> [25] 0.312177167 0.223557946 0.743130328 0.292035585 0.194360413 0.014731338
#> [31] 0.876284020 0.470835908 0.520627463 0.632226691 0.551138338 0.632226691
#> [37] 0.400513554 0.540902905 0.030519434 0.030519434 0.126948277 0.917748501
#> [43] 0.420670767 0.917748501 0.204167461 0.682075325 0.233466254 0.743130328
#> [49] 0.440579186 0.460754203 0.076822669 0.886662764 0.561359988 0.066879363
#> [55] 0.743130328 0.146078631 0.897036196 0.184614883 0.804138912 0.510433842
#> [61] 0.470835908 0.420670767 0.917748501 0.591415045 0.632226691 0.591415045
#> [67] 0.253032399 0.520627463 0.969075329 0.281989814 0.086812071 0.948406961
#> [73] 0.390465886 0.722858269 0.096916562 0.561359988 0.632226691 0.979408762
#> [79] 0.253032399 0.116916938 0.845195506 0.370656583 0.253032399 0.340917604
#> [85] 0.814479582 0.106859243 0.004714711 0.979408762 0.312177167 0.312177167
#> [91] 0.470835908 0.743130328 0.126948277 0.174807796 0.958750092 0.814479582
#> [97] 0.632226691 0.048266442 0.722858269 0.611717632 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 60 164 123 86 187 56 110 159 56.1 30 36 43 111
#> 13.15 23.60 13.00 23.81 9.92 12.21 17.56 10.55 12.21 17.43 21.19 12.10 17.45
#> 41 155 150 100 10 106 85 153 58 29 96 40 158
#> 18.02 13.08 20.33 16.07 10.53 16.67 16.44 21.33 19.34 15.45 14.54 18.00 20.14
#> 177 88 68 86.1 52 100.1 6 13 167 13.1 23 39 168
#> 12.53 18.37 20.62 23.81 10.42 16.07 15.64 14.34 15.55 14.34 16.92 15.59 23.72
#> 168.1 139 183 171 183.1 150.1 60.1 55 177.1 181 79 92 145
#> 23.72 21.49 9.24 16.57 9.24 20.33 13.15 19.34 12.53 16.46 16.23 22.92 10.07
#> 29.1 129 177.2 153.1 101 190 49 125 100.2 171.1 183.2 157 13.2
#> 15.45 23.41 12.53 21.33 9.97 20.81 12.19 15.65 16.07 16.57 9.24 15.10 14.34
#> 157.1 76 6.1 91 179 113 16 45 140 63 29.2 13.3 127
#> 15.10 19.22 15.64 5.33 18.63 22.86 8.71 17.42 12.68 22.77 15.45 14.34 3.53
#> 76.1 197 107 30.1 76.2 184 43.1 175 78 127.1 40.1 40.2 100.3
#> 19.22 21.60 11.18 17.43 19.22 17.77 12.10 21.91 23.88 3.53 18.00 18.00 16.07
#> 177.3 139.1 90 70 43.2 13.4 164.1 140.1 180 75 44 141 102
#> 12.53 21.49 20.94 7.38 12.10 14.34 23.60 12.68 14.82 24.00 24.00 24.00 24.00
#> 178 44.1 200 162 135 141.1 172 67 152 53 116 137 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 20 74 185 7 21 48 131 72 103 122 186 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 34 200.1 138.1 132 2 46 103.1 172.1 7.1 162.1 186.1 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.2 35 82 165 71 67.1 161 17 27 53.1 151 87 162.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 160 1 160.1 198 182 19 19.1 147 121 173 191 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1 172.2 44.2 174 94.1 126 193 17.1 160.2 11 21.1 146 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 44.3 1.1
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[55]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01468591 0.83648348 0.10829799
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.077572457 -0.001185705 0.200701665
#> grade_iii, Cure model
#> 0.447938212
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 79 16.23 1 54 1 0
#> 145 10.07 1 65 1 0
#> 90 20.94 1 50 0 1
#> 88 18.37 1 47 0 0
#> 68 20.62 1 44 0 0
#> 180 14.82 1 37 0 0
#> 154 12.63 1 20 1 0
#> 169 22.41 1 46 0 0
#> 60 13.15 1 38 1 0
#> 90.1 20.94 1 50 0 1
#> 133 14.65 1 57 0 0
#> 14 12.89 1 21 0 0
#> 129 23.41 1 53 1 0
#> 150 20.33 1 48 0 0
#> 189 10.51 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 6 15.64 1 39 0 0
#> 164 23.60 1 76 0 1
#> 16 8.71 1 71 0 1
#> 76 19.22 1 54 0 1
#> 180.1 14.82 1 37 0 0
#> 32 20.90 1 37 1 0
#> 79.1 16.23 1 54 1 0
#> 86 23.81 1 58 0 1
#> 81 14.06 1 34 0 0
#> 60.1 13.15 1 38 1 0
#> 187 9.92 1 39 1 0
#> 13 14.34 1 54 0 1
#> 169.1 22.41 1 46 0 0
#> 183 9.24 1 67 1 0
#> 68.1 20.62 1 44 0 0
#> 111 17.45 1 47 0 1
#> 195 11.76 1 NA 1 0
#> 14.1 12.89 1 21 0 0
#> 14.2 12.89 1 21 0 0
#> 136 21.83 1 43 0 1
#> 86.1 23.81 1 58 0 1
#> 14.3 12.89 1 21 0 0
#> 51 18.23 1 83 0 1
#> 199 19.81 1 NA 0 1
#> 171 16.57 1 41 0 1
#> 24 23.89 1 38 0 0
#> 123 13.00 1 44 1 0
#> 155 13.08 1 26 0 0
#> 89 11.44 1 NA 0 0
#> 52 10.42 1 52 0 1
#> 43 12.10 1 61 0 1
#> 197 21.60 1 69 1 0
#> 154.1 12.63 1 20 1 0
#> 14.4 12.89 1 21 0 0
#> 159 10.55 1 50 0 1
#> 117 17.46 1 26 0 1
#> 10 10.53 1 34 0 0
#> 175 21.91 1 43 0 0
#> 177 12.53 1 75 0 0
#> 60.2 13.15 1 38 1 0
#> 100 16.07 1 60 0 0
#> 16.1 8.71 1 71 0 1
#> 57 14.46 1 45 0 1
#> 86.2 23.81 1 58 0 1
#> 25 6.32 1 34 1 0
#> 136.1 21.83 1 43 0 1
#> 70 7.38 1 30 1 0
#> 184 17.77 1 38 0 0
#> 107.1 11.18 1 54 1 0
#> 117.1 17.46 1 26 0 1
#> 110 17.56 1 65 0 1
#> 70.1 7.38 1 30 1 0
#> 15 22.68 1 48 0 0
#> 117.2 17.46 1 26 0 1
#> 68.2 20.62 1 44 0 0
#> 37 12.52 1 57 1 0
#> 134 17.81 1 47 1 0
#> 194 22.40 1 38 0 1
#> 66 22.13 1 53 0 0
#> 55 19.34 1 69 0 1
#> 153 21.33 1 55 1 0
#> 55.1 19.34 1 69 0 1
#> 56 12.21 1 60 0 0
#> 117.3 17.46 1 26 0 1
#> 58 19.34 1 39 0 0
#> 159.1 10.55 1 50 0 1
#> 40 18.00 1 28 1 0
#> 181 16.46 1 45 0 1
#> 123.1 13.00 1 44 1 0
#> 58.1 19.34 1 39 0 0
#> 117.4 17.46 1 26 0 1
#> 133.1 14.65 1 57 0 0
#> 68.3 20.62 1 44 0 0
#> 81.1 14.06 1 34 0 0
#> 117.5 17.46 1 26 0 1
#> 101 9.97 1 10 0 1
#> 154.2 12.63 1 20 1 0
#> 69 23.23 1 25 0 1
#> 114 13.68 1 NA 0 0
#> 70.2 7.38 1 30 1 0
#> 16.2 8.71 1 71 0 1
#> 24.1 23.89 1 38 0 0
#> 99 21.19 1 38 0 1
#> 194.1 22.40 1 38 0 1
#> 42 12.43 1 49 0 1
#> 133.2 14.65 1 57 0 0
#> 91 5.33 1 61 0 1
#> 66.1 22.13 1 53 0 0
#> 149 8.37 1 33 1 0
#> 149.1 8.37 1 33 1 0
#> 128 20.35 1 35 0 1
#> 52.1 10.42 1 52 0 1
#> 197.1 21.60 1 69 1 0
#> 8 18.43 1 32 0 0
#> 125 15.65 1 67 1 0
#> 195.1 11.76 1 NA 1 0
#> 94 24.00 0 51 0 1
#> 47 24.00 0 38 0 1
#> 115 24.00 0 NA 1 0
#> 162 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 147 24.00 0 76 1 0
#> 176 24.00 0 43 0 1
#> 186 24.00 0 45 1 0
#> 119 24.00 0 17 0 0
#> 73 24.00 0 NA 0 1
#> 161 24.00 0 45 0 0
#> 21 24.00 0 47 0 0
#> 2 24.00 0 9 0 0
#> 19 24.00 0 57 0 1
#> 196 24.00 0 19 0 0
#> 94.1 24.00 0 51 0 1
#> 94.2 24.00 0 51 0 1
#> 54 24.00 0 53 1 0
#> 142 24.00 0 53 0 0
#> 200 24.00 0 64 0 0
#> 3 24.00 0 31 1 0
#> 54.1 24.00 0 53 1 0
#> 54.2 24.00 0 53 1 0
#> 173 24.00 0 19 0 1
#> 17 24.00 0 38 0 1
#> 73.1 24.00 0 NA 0 1
#> 142.1 24.00 0 53 0 0
#> 62 24.00 0 71 0 0
#> 22 24.00 0 52 1 0
#> 176.1 24.00 0 43 0 1
#> 160 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 38 24.00 0 31 1 0
#> 21.1 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 131 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 11 24.00 0 42 0 1
#> 44 24.00 0 56 0 0
#> 54.3 24.00 0 53 1 0
#> 119.1 24.00 0 17 0 0
#> 73.2 24.00 0 NA 0 1
#> 196.1 24.00 0 19 0 0
#> 33 24.00 0 53 0 0
#> 65 24.00 0 57 1 0
#> 161.1 24.00 0 45 0 0
#> 82 24.00 0 34 0 0
#> 186.1 24.00 0 45 1 0
#> 143 24.00 0 51 0 0
#> 38.1 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 33.1 24.00 0 53 0 0
#> 80 24.00 0 41 0 0
#> 47.1 24.00 0 38 0 1
#> 28 24.00 0 67 1 0
#> 7.1 24.00 0 37 1 0
#> 3.1 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 152 24.00 0 36 0 1
#> 72.1 24.00 0 40 0 1
#> 94.3 24.00 0 51 0 1
#> 83 24.00 0 6 0 0
#> 119.2 24.00 0 17 0 0
#> 84.1 24.00 0 39 0 1
#> 176.2 24.00 0 43 0 1
#> 104 24.00 0 50 1 0
#> 94.4 24.00 0 51 0 1
#> 142.2 24.00 0 53 0 0
#> 147.1 24.00 0 76 1 0
#> 84.2 24.00 0 39 0 1
#> 146 24.00 0 63 1 0
#> 83.1 24.00 0 6 0 0
#> 9 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 161.2 24.00 0 45 0 0
#> 148 24.00 0 61 1 0
#> 35 24.00 0 51 0 0
#> 28.1 24.00 0 67 1 0
#> 142.3 24.00 0 53 0 0
#> 21.2 24.00 0 47 0 0
#> 135 24.00 0 58 1 0
#> 165 24.00 0 47 0 0
#> 83.2 24.00 0 6 0 0
#> 53 24.00 0 32 0 1
#> 84.3 24.00 0 39 0 1
#> 109 24.00 0 48 0 0
#> 19.1 24.00 0 57 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0776 NA NA NA
#> 2 age, Cure model -0.00119 NA NA NA
#> 3 grade_ii, Cure model 0.201 NA NA NA
#> 4 grade_iii, Cure model 0.448 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0147 NA NA NA
#> 2 grade_ii, Survival model 0.836 NA NA NA
#> 3 grade_iii, Survival model 0.108 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.077572 -0.001186 0.200702 0.447938
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 259.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.077572457 -0.001185705 0.200701665 0.447938212
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01468591 0.83648348 0.10829799
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.3580086094 0.8246432899 0.0944124757 0.2116613217 0.1152789231
#> [6] 0.4115492998 0.6448684554 0.0222236738 0.5158243810 0.0944124757
#> [11] 0.4336785317 0.5863042586 0.0116012694 0.1517975089 0.7389715319
#> [16] 0.4005825592 0.0082524947 0.8748484459 0.1932277229 0.4115492998
#> [21] 0.1082705125 0.3580086094 0.0025693469 0.4917130047 0.5158243810
#> [26] 0.8497857100 0.4797395698 0.0222236738 0.8623045916 0.1152789231
#> [31] 0.3264415284 0.5863042586 0.5863042586 0.0563416763 0.0025693469
#> [36] 0.5863042586 0.2211649514 0.3368338916 0.0004476984 0.5627818089
#> [41] 0.5507889347 0.7997415017 0.7268421759 0.0685589205 0.6448684554
#> [46] 0.5863042586 0.7629964950 0.2695798969 0.7873786997 0.0504200863
#> [51] 0.6792968419 0.5158243810 0.3789490110 0.8748484459 0.4679124878
#> [56] 0.0025693469 0.9751098355 0.0563416763 0.9381881584 0.2500326909
#> [61] 0.7389715319 0.2695798969 0.2597012851 0.9381881584 0.0183772636
#> [66] 0.2695798969 0.1152789231 0.6911080330 0.2405214223 0.0305585641
#> [71] 0.0398196949 0.1599130291 0.0811448751 0.1599130291 0.7148221497
#> [76] 0.2695798969 0.1599130291 0.7629964950 0.2309506093 0.3473527474
#> [81] 0.5627818089 0.1599130291 0.2695798969 0.4336785317 0.1152789231
#> [86] 0.4917130047 0.2695798969 0.8372109280 0.6448684554 0.0149001863
#> [91] 0.9381881584 0.8748484459 0.0004476984 0.0876877228 0.0305585641
#> [96] 0.7029193527 0.4336785317 0.9875121762 0.0398196949 0.9129233537
#> [101] 0.9129233537 0.1438957355 0.7997415017 0.0685589205 0.2023658035
#> [106] 0.3897451959 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 79 145 90 88 68 180 154 169 60 90.1 133 14 129
#> 16.23 10.07 20.94 18.37 20.62 14.82 12.63 22.41 13.15 20.94 14.65 12.89 23.41
#> 150 107 6 164 16 76 180.1 32 79.1 86 81 60.1 187
#> 20.33 11.18 15.64 23.60 8.71 19.22 14.82 20.90 16.23 23.81 14.06 13.15 9.92
#> 13 169.1 183 68.1 111 14.1 14.2 136 86.1 14.3 51 171 24
#> 14.34 22.41 9.24 20.62 17.45 12.89 12.89 21.83 23.81 12.89 18.23 16.57 23.89
#> 123 155 52 43 197 154.1 14.4 159 117 10 175 177 60.2
#> 13.00 13.08 10.42 12.10 21.60 12.63 12.89 10.55 17.46 10.53 21.91 12.53 13.15
#> 100 16.1 57 86.2 25 136.1 70 184 107.1 117.1 110 70.1 15
#> 16.07 8.71 14.46 23.81 6.32 21.83 7.38 17.77 11.18 17.46 17.56 7.38 22.68
#> 117.2 68.2 37 134 194 66 55 153 55.1 56 117.3 58 159.1
#> 17.46 20.62 12.52 17.81 22.40 22.13 19.34 21.33 19.34 12.21 17.46 19.34 10.55
#> 40 181 123.1 58.1 117.4 133.1 68.3 81.1 117.5 101 154.2 69 70.2
#> 18.00 16.46 13.00 19.34 17.46 14.65 20.62 14.06 17.46 9.97 12.63 23.23 7.38
#> 16.2 24.1 99 194.1 42 133.2 91 66.1 149 149.1 128 52.1 197.1
#> 8.71 23.89 21.19 22.40 12.43 14.65 5.33 22.13 8.37 8.37 20.35 10.42 21.60
#> 8 125 94 47 162 191 147 176 186 119 161 21 2
#> 18.43 15.65 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 196 94.1 94.2 54 142 200 3 54.1 54.2 173 17 142.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 22 176.1 160 72 38 21.1 12 131 84 11 44 54.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 196.1 33 65 161.1 82 186.1 143 38.1 7 33.1 80 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 7.1 3.1 122 95 152 72.1 94.3 83 119.2 84.1 176.2 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.4 142.2 147.1 84.2 146 83.1 9 64 161.2 148 35 28.1 142.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.2 135 165 83.2 53 84.3 109 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[56]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006035963 0.667353278 0.198650332
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.53046764 0.01037109 -0.02192299
#> grade_iii, Cure model
#> 0.70432694
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 90 20.94 1 50 0 1
#> 14 12.89 1 21 0 0
#> 13 14.34 1 54 0 1
#> 42 12.43 1 49 0 1
#> 105 19.75 1 60 0 0
#> 127 3.53 1 62 0 1
#> 97 19.14 1 65 0 1
#> 195 11.76 1 NA 1 0
#> 97.1 19.14 1 65 0 1
#> 139 21.49 1 63 1 0
#> 37 12.52 1 57 1 0
#> 43 12.10 1 61 0 1
#> 10 10.53 1 34 0 0
#> 125 15.65 1 67 1 0
#> 130 16.47 1 53 0 1
#> 26 15.77 1 49 0 1
#> 6 15.64 1 39 0 0
#> 170 19.54 1 43 0 1
#> 25 6.32 1 34 1 0
#> 171 16.57 1 41 0 1
#> 194 22.40 1 38 0 1
#> 70 7.38 1 30 1 0
#> 78 23.88 1 43 0 0
#> 189 10.51 1 NA 1 0
#> 81 14.06 1 34 0 0
#> 56 12.21 1 60 0 0
#> 55 19.34 1 69 0 1
#> 30 17.43 1 78 0 0
#> 195.1 11.76 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 97.2 19.14 1 65 0 1
#> 140 12.68 1 59 1 0
#> 13.1 14.34 1 54 0 1
#> 78.1 23.88 1 43 0 0
#> 127.1 3.53 1 62 0 1
#> 85 16.44 1 36 0 0
#> 6.1 15.64 1 39 0 0
#> 59 10.16 1 NA 1 0
#> 123 13.00 1 44 1 0
#> 6.2 15.64 1 39 0 0
#> 153 21.33 1 55 1 0
#> 169 22.41 1 46 0 0
#> 13.2 14.34 1 54 0 1
#> 153.1 21.33 1 55 1 0
#> 153.2 21.33 1 55 1 0
#> 199 19.81 1 NA 0 1
#> 4 17.64 1 NA 0 1
#> 78.2 23.88 1 43 0 0
#> 190 20.81 1 42 1 0
#> 91 5.33 1 61 0 1
#> 61 10.12 1 36 0 1
#> 195.2 11.76 1 NA 1 0
#> 190.1 20.81 1 42 1 0
#> 90.1 20.94 1 50 0 1
#> 153.3 21.33 1 55 1 0
#> 106 16.67 1 49 1 0
#> 97.3 19.14 1 65 0 1
#> 130.1 16.47 1 53 0 1
#> 149 8.37 1 33 1 0
#> 99 21.19 1 38 0 1
#> 78.3 23.88 1 43 0 0
#> 92 22.92 1 47 0 1
#> 93 10.33 1 52 0 1
#> 181 16.46 1 45 0 1
#> 92.1 22.92 1 47 0 1
#> 30.1 17.43 1 78 0 0
#> 15 22.68 1 48 0 0
#> 171.1 16.57 1 41 0 1
#> 125.1 15.65 1 67 1 0
#> 155 13.08 1 26 0 0
#> 197 21.60 1 69 1 0
#> 136 21.83 1 43 0 1
#> 175 21.91 1 43 0 0
#> 101 9.97 1 10 0 1
#> 88 18.37 1 47 0 0
#> 164 23.60 1 76 0 1
#> 125.2 15.65 1 67 1 0
#> 10.1 10.53 1 34 0 0
#> 23 16.92 1 61 0 0
#> 108 18.29 1 39 0 1
#> 88.1 18.37 1 47 0 0
#> 79 16.23 1 54 1 0
#> 85.1 16.44 1 36 0 0
#> 79.1 16.23 1 54 1 0
#> 86 23.81 1 58 0 1
#> 107 11.18 1 54 1 0
#> 177 12.53 1 75 0 0
#> 49 12.19 1 48 1 0
#> 6.3 15.64 1 39 0 0
#> 37.1 12.52 1 57 1 0
#> 30.2 17.43 1 78 0 0
#> 91.1 5.33 1 61 0 1
#> 179 18.63 1 42 0 0
#> 136.1 21.83 1 43 0 1
#> 140.1 12.68 1 59 1 0
#> 45 17.42 1 54 0 1
#> 18 15.21 1 49 1 0
#> 169.1 22.41 1 46 0 0
#> 69 23.23 1 25 0 1
#> 16 8.71 1 71 0 1
#> 128.1 20.35 1 35 0 1
#> 92.2 22.92 1 47 0 1
#> 60 13.15 1 38 1 0
#> 187 9.92 1 39 1 0
#> 159 10.55 1 50 0 1
#> 150 20.33 1 48 0 0
#> 86.1 23.81 1 58 0 1
#> 180 14.82 1 37 0 0
#> 6.4 15.64 1 39 0 0
#> 93.1 10.33 1 52 0 1
#> 66 22.13 1 53 0 0
#> 10.2 10.53 1 34 0 0
#> 94 24.00 0 51 0 1
#> 198 24.00 0 66 0 1
#> 53 24.00 0 32 0 1
#> 109 24.00 0 48 0 0
#> 33 24.00 0 53 0 0
#> 147 24.00 0 76 1 0
#> 38 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 33.1 24.00 0 53 0 0
#> 87 24.00 0 27 0 0
#> 102 24.00 0 49 0 0
#> 27 24.00 0 63 1 0
#> 147.1 24.00 0 76 1 0
#> 152 24.00 0 36 0 1
#> 186 24.00 0 45 1 0
#> 71 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 82 24.00 0 34 0 0
#> 21 24.00 0 47 0 0
#> 54 24.00 0 53 1 0
#> 132 24.00 0 55 0 0
#> 104 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 160 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 98.1 24.00 0 34 1 0
#> 186.1 24.00 0 45 1 0
#> 102.1 24.00 0 49 0 0
#> 185 24.00 0 44 1 0
#> 198.1 24.00 0 66 0 1
#> 193 24.00 0 45 0 1
#> 116 24.00 0 58 0 1
#> 38.1 24.00 0 31 1 0
#> 54.1 24.00 0 53 1 0
#> 34 24.00 0 36 0 0
#> 67 24.00 0 25 0 0
#> 64 24.00 0 43 0 0
#> 172 24.00 0 41 0 0
#> 193.1 24.00 0 45 0 1
#> 182 24.00 0 35 0 0
#> 31 24.00 0 36 0 1
#> 165 24.00 0 47 0 0
#> 165.1 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 83 24.00 0 6 0 0
#> 138 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 174 24.00 0 49 1 0
#> 148 24.00 0 61 1 0
#> 143.1 24.00 0 51 0 0
#> 95 24.00 0 68 0 1
#> 122 24.00 0 66 0 0
#> 12.1 24.00 0 63 0 0
#> 9 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 147.2 24.00 0 76 1 0
#> 120 24.00 0 68 0 1
#> 47 24.00 0 38 0 1
#> 12.2 24.00 0 63 0 0
#> 19 24.00 0 57 0 1
#> 84.1 24.00 0 39 0 1
#> 138.1 24.00 0 44 1 0
#> 156 24.00 0 50 1 0
#> 178 24.00 0 52 1 0
#> 73.1 24.00 0 NA 0 1
#> 185.1 24.00 0 44 1 0
#> 87.1 24.00 0 27 0 0
#> 109.1 24.00 0 48 0 0
#> 143.2 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 178.1 24.00 0 52 1 0
#> 17 24.00 0 38 0 1
#> 196 24.00 0 19 0 0
#> 64.1 24.00 0 43 0 0
#> 120.1 24.00 0 68 0 1
#> 165.2 24.00 0 47 0 0
#> 94.1 24.00 0 51 0 1
#> 173 24.00 0 19 0 1
#> 44 24.00 0 56 0 0
#> 7 24.00 0 37 1 0
#> 22.1 24.00 0 52 1 0
#> 95.1 24.00 0 68 0 1
#> 126 24.00 0 48 0 0
#> 95.2 24.00 0 68 0 1
#> 182.1 24.00 0 35 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.530 NA NA NA
#> 2 age, Cure model 0.0104 NA NA NA
#> 3 grade_ii, Cure model -0.0219 NA NA NA
#> 4 grade_iii, Cure model 0.704 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00604 NA NA NA
#> 2 grade_ii, Survival model 0.667 NA NA NA
#> 3 grade_iii, Survival model 0.199 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.53047 0.01037 -0.02192 0.70433
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 256.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.53046764 0.01037109 -0.02192299 0.70432694
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006035963 0.667353278 0.198650332
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.241342158 0.730225015 0.661511701 0.788351917 0.304938077 0.980969905
#> [7] 0.332807382 0.332807382 0.186326061 0.769127322 0.817418074 0.846385996
#> [13] 0.565131709 0.486023929 0.555224718 0.593888215 0.314199597 0.952495817
#> [19] 0.466393410 0.123896682 0.942936525 0.008901206 0.690783027 0.798034535
#> [25] 0.323477293 0.407525243 0.277830114 0.332807382 0.740042184 0.661511701
#> [31] 0.008901206 0.980969905 0.515718169 0.593888215 0.720423535 0.593888215
#> [37] 0.196611887 0.104342400 0.661511701 0.196611887 0.196611887 0.008901206
#> [43] 0.259913859 0.961999082 0.894532341 0.259913859 0.241342158 0.196611887
#> [49] 0.456492769 0.332807382 0.486023929 0.933316157 0.231943104 0.008901206
#> [55] 0.068656194 0.875181818 0.505745504 0.068656194 0.407525243 0.094532622
#> [61] 0.466393410 0.565131709 0.710555673 0.175848087 0.155176506 0.144560148
#> [67] 0.904262456 0.378812988 0.049343231 0.565131709 0.846385996 0.446494551
#> [73] 0.397870902 0.378812988 0.535619599 0.515718169 0.535619599 0.032541907
#> [79] 0.827101023 0.759360441 0.807752981 0.593888215 0.769127322 0.407525243
#> [85] 0.961999082 0.369281140 0.155176506 0.740042184 0.436564829 0.641838011
#> [91] 0.104342400 0.059036471 0.923636217 0.277830114 0.068656194 0.700707677
#> [97] 0.913977069 0.836738064 0.295761254 0.032541907 0.651659995 0.593888215
#> [103] 0.875181818 0.134119334 0.846385996 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 90 14 13 42 105 127 97 97.1 139 37 43 10 125
#> 20.94 12.89 14.34 12.43 19.75 3.53 19.14 19.14 21.49 12.52 12.10 10.53 15.65
#> 130 26 6 170 25 171 194 70 78 81 56 55 30
#> 16.47 15.77 15.64 19.54 6.32 16.57 22.40 7.38 23.88 14.06 12.21 19.34 17.43
#> 128 97.2 140 13.1 78.1 127.1 85 6.1 123 6.2 153 169 13.2
#> 20.35 19.14 12.68 14.34 23.88 3.53 16.44 15.64 13.00 15.64 21.33 22.41 14.34
#> 153.1 153.2 78.2 190 91 61 190.1 90.1 153.3 106 97.3 130.1 149
#> 21.33 21.33 23.88 20.81 5.33 10.12 20.81 20.94 21.33 16.67 19.14 16.47 8.37
#> 99 78.3 92 93 181 92.1 30.1 15 171.1 125.1 155 197 136
#> 21.19 23.88 22.92 10.33 16.46 22.92 17.43 22.68 16.57 15.65 13.08 21.60 21.83
#> 175 101 88 164 125.2 10.1 23 108 88.1 79 85.1 79.1 86
#> 21.91 9.97 18.37 23.60 15.65 10.53 16.92 18.29 18.37 16.23 16.44 16.23 23.81
#> 107 177 49 6.3 37.1 30.2 91.1 179 136.1 140.1 45 18 169.1
#> 11.18 12.53 12.19 15.64 12.52 17.43 5.33 18.63 21.83 12.68 17.42 15.21 22.41
#> 69 16 128.1 92.2 60 187 159 150 86.1 180 6.4 93.1 66
#> 23.23 8.71 20.35 22.92 13.15 9.92 10.55 20.33 23.81 14.82 15.64 10.33 22.13
#> 10.2 94 198 53 109 33 147 38 35 11 33.1 87 102
#> 10.53 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 147.1 152 186 71 48 22 82 21 54 132 104 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 160 162 98.1 186.1 102.1 185 198.1 193 116 38.1 54.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 64 172 193.1 182 31 165 165.1 12 83 138 84 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 143.1 95 122 12.1 9 147.2 120 47 12.2 19 84.1 138.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 178 185.1 87.1 109.1 143.2 161 178.1 17 196 64.1 120.1 165.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 173 44 7 22.1 95.1 126 95.2 182.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[57]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.008864072 0.803679603 0.559381508
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.97501686 0.01837444 0.12028082
#> grade_iii, Cure model
#> 0.96825482
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 24 23.89 1 38 0 0
#> 136 21.83 1 43 0 1
#> 89 11.44 1 NA 0 0
#> 79 16.23 1 54 1 0
#> 4 17.64 1 NA 0 1
#> 153 21.33 1 55 1 0
#> 78 23.88 1 43 0 0
#> 56 12.21 1 60 0 0
#> 96 14.54 1 33 0 1
#> 42 12.43 1 49 0 1
#> 150 20.33 1 48 0 0
#> 140 12.68 1 59 1 0
#> 4.1 17.64 1 NA 0 1
#> 124 9.73 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 149 8.37 1 33 1 0
#> 187 9.92 1 39 1 0
#> 42.1 12.43 1 49 0 1
#> 59 10.16 1 NA 1 0
#> 124.1 9.73 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 154 12.63 1 20 1 0
#> 6 15.64 1 39 0 0
#> 93 10.33 1 52 0 1
#> 140.1 12.68 1 59 1 0
#> 124.2 9.73 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 177 12.53 1 75 0 0
#> 134 17.81 1 47 1 0
#> 134.1 17.81 1 47 1 0
#> 128 20.35 1 35 0 1
#> 24.1 23.89 1 38 0 0
#> 45 17.42 1 54 0 1
#> 124.3 9.73 1 NA 1 0
#> 43 12.10 1 61 0 1
#> 68 20.62 1 44 0 0
#> 99 21.19 1 38 0 1
#> 108 18.29 1 39 0 1
#> 92.1 22.92 1 47 0 1
#> 187.1 9.92 1 39 1 0
#> 100 16.07 1 60 0 0
#> 107 11.18 1 54 1 0
#> 81 14.06 1 34 0 0
#> 179 18.63 1 42 0 0
#> 61 10.12 1 36 0 1
#> 179.1 18.63 1 42 0 0
#> 184 17.77 1 38 0 0
#> 42.2 12.43 1 49 0 1
#> 29 15.45 1 68 1 0
#> 180 14.82 1 37 0 0
#> 150.1 20.33 1 48 0 0
#> 164 23.60 1 76 0 1
#> 105 19.75 1 60 0 0
#> 125 15.65 1 67 1 0
#> 188.1 16.16 1 46 0 1
#> 52 10.42 1 52 0 1
#> 91 5.33 1 61 0 1
#> 63 22.77 1 31 1 0
#> 57 14.46 1 45 0 1
#> 79.1 16.23 1 54 1 0
#> 114 13.68 1 NA 0 0
#> 14 12.89 1 21 0 0
#> 79.2 16.23 1 54 1 0
#> 36 21.19 1 48 0 1
#> 154.1 12.63 1 20 1 0
#> 85 16.44 1 36 0 0
#> 171 16.57 1 41 0 1
#> 57.1 14.46 1 45 0 1
#> 5 16.43 1 51 0 1
#> 136.1 21.83 1 43 0 1
#> 168 23.72 1 70 0 0
#> 181 16.46 1 45 0 1
#> 189 10.51 1 NA 1 0
#> 177.1 12.53 1 75 0 0
#> 184.1 17.77 1 38 0 0
#> 49 12.19 1 48 1 0
#> 58 19.34 1 39 0 0
#> 37 12.52 1 57 1 0
#> 145 10.07 1 65 1 0
#> 170 19.54 1 43 0 1
#> 100.1 16.07 1 60 0 0
#> 140.2 12.68 1 59 1 0
#> 134.2 17.81 1 47 1 0
#> 179.2 18.63 1 42 0 0
#> 69 23.23 1 25 0 1
#> 93.1 10.33 1 52 0 1
#> 70 7.38 1 30 1 0
#> 63.1 22.77 1 31 1 0
#> 68.1 20.62 1 44 0 0
#> 13 14.34 1 54 0 1
#> 37.1 12.52 1 57 1 0
#> 177.2 12.53 1 75 0 0
#> 183 9.24 1 67 1 0
#> 133 14.65 1 57 0 0
#> 79.3 16.23 1 54 1 0
#> 123 13.00 1 44 1 0
#> 96.1 14.54 1 33 0 1
#> 197 21.60 1 69 1 0
#> 66 22.13 1 53 0 0
#> 139 21.49 1 63 1 0
#> 76 19.22 1 54 0 1
#> 43.1 12.10 1 61 0 1
#> 78.1 23.88 1 43 0 0
#> 78.2 23.88 1 43 0 0
#> 32 20.90 1 37 1 0
#> 167 15.55 1 56 1 0
#> 190 20.81 1 42 1 0
#> 167.1 15.55 1 56 1 0
#> 59.1 10.16 1 NA 1 0
#> 61.1 10.12 1 36 0 1
#> 154.2 12.63 1 20 1 0
#> 66.1 22.13 1 53 0 0
#> 84 24.00 0 39 0 1
#> 20 24.00 0 46 1 0
#> 135 24.00 0 58 1 0
#> 48 24.00 0 31 1 0
#> 20.1 24.00 0 46 1 0
#> 131 24.00 0 66 0 0
#> 3 24.00 0 31 1 0
#> 135.1 24.00 0 58 1 0
#> 200 24.00 0 64 0 0
#> 64 24.00 0 43 0 0
#> 21 24.00 0 47 0 0
#> 47 24.00 0 38 0 1
#> 162 24.00 0 51 0 0
#> 131.1 24.00 0 66 0 0
#> 44 24.00 0 56 0 0
#> 115 24.00 0 NA 1 0
#> 12 24.00 0 63 0 0
#> 152 24.00 0 36 0 1
#> 172 24.00 0 41 0 0
#> 1 24.00 0 23 1 0
#> 9 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 31 24.00 0 36 0 1
#> 1.1 24.00 0 23 1 0
#> 176 24.00 0 43 0 1
#> 65 24.00 0 57 1 0
#> 98 24.00 0 34 1 0
#> 71 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 38 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 72 24.00 0 40 0 1
#> 38.1 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 173 24.00 0 19 0 1
#> 109 24.00 0 48 0 0
#> 196 24.00 0 19 0 0
#> 73 24.00 0 NA 0 1
#> 21.1 24.00 0 47 0 0
#> 44.1 24.00 0 56 0 0
#> 119 24.00 0 17 0 0
#> 122 24.00 0 66 0 0
#> 148.1 24.00 0 61 1 0
#> 2 24.00 0 9 0 0
#> 48.1 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 84.1 24.00 0 39 0 1
#> 103 24.00 0 56 1 0
#> 156 24.00 0 50 1 0
#> 176.1 24.00 0 43 0 1
#> 12.1 24.00 0 63 0 0
#> 142 24.00 0 53 0 0
#> 118 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 132 24.00 0 55 0 0
#> 165 24.00 0 47 0 0
#> 28 24.00 0 67 1 0
#> 9.1 24.00 0 31 1 0
#> 142.1 24.00 0 53 0 0
#> 9.2 24.00 0 31 1 0
#> 22.1 24.00 0 52 1 0
#> 33.1 24.00 0 53 0 0
#> 161 24.00 0 45 0 0
#> 22.2 24.00 0 52 1 0
#> 137 24.00 0 45 1 0
#> 191 24.00 0 60 0 1
#> 196.1 24.00 0 19 0 0
#> 3.1 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 21.2 24.00 0 47 0 0
#> 178 24.00 0 52 1 0
#> 74 24.00 0 43 0 1
#> 115.1 24.00 0 NA 1 0
#> 47.1 24.00 0 38 0 1
#> 131.2 24.00 0 66 0 0
#> 71.1 24.00 0 51 0 0
#> 191.1 24.00 0 60 0 1
#> 104 24.00 0 50 1 0
#> 161.1 24.00 0 45 0 0
#> 122.1 24.00 0 66 0 0
#> 67 24.00 0 25 0 0
#> 65.1 24.00 0 57 1 0
#> 67.1 24.00 0 25 0 0
#> 174 24.00 0 49 1 0
#> 54 24.00 0 53 1 0
#> 109.1 24.00 0 48 0 0
#> 172.1 24.00 0 41 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.975 NA NA NA
#> 2 age, Cure model 0.0184 NA NA NA
#> 3 grade_ii, Cure model 0.120 NA NA NA
#> 4 grade_iii, Cure model 0.968 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00886 NA NA NA
#> 2 grade_ii, Survival model 0.804 NA NA NA
#> 3 grade_iii, Survival model 0.559 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.97502 0.01837 0.12028 0.96825
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.5
#> Residual Deviance: 247.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.97501686 0.01837444 0.12028082 0.96825482
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.008864072 0.803679603 0.559381508
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.08654009 0.44441378 0.73642132 0.49525969 0.17673203 0.93050762
#> [7] 0.82408790 0.91731083 0.57320192 0.86576722 0.76092381 0.98844587
#> [13] 0.97663279 0.91731083 0.34739020 0.88026195 0.79069870 0.95622069
#> [19] 0.86576722 0.70156559 0.89436944 0.65774268 0.65774268 0.56412488
#> [25] 0.08654009 0.69435698 0.93926839 0.54570950 0.50618312 0.64967561
#> [31] 0.34739020 0.97663279 0.77295686 0.94780108 0.85039492 0.62533427
#> [37] 0.96446096 0.62533427 0.67973930 0.91731083 0.80768544 0.81317045
#> [43] 0.57320192 0.29951776 0.59091714 0.78485983 0.76092381 0.95202739
#> [49] 0.99617798 0.38397230 0.83475650 0.73642132 0.86067089 0.73642132
#> [55] 0.50618312 0.88026195 0.72270761 0.70872147 0.83475650 0.72962083
#> [61] 0.44441378 0.26819391 0.71576943 0.89436944 0.67973930 0.93491282
#> [67] 0.60838140 0.90826993 0.97260333 0.59974851 0.77295686 0.86576722
#> [73] 0.65774268 0.62533427 0.32449604 0.95622069 0.99232634 0.38397230
#> [79] 0.54570950 0.84521037 0.90826993 0.89436944 0.98453480 0.81864114
#> [85] 0.73642132 0.85556837 0.82408790 0.47119553 0.41485203 0.48366170
#> [91] 0.61696401 0.93926839 0.17673203 0.17673203 0.52644192 0.79651982
#> [97] 0.53626957 0.79651982 0.96446096 0.88026195 0.41485203 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 24 136 79 153 78 56 96 42 150 140 188 149 187
#> 23.89 21.83 16.23 21.33 23.88 12.21 14.54 12.43 20.33 12.68 16.16 8.37 9.92
#> 42.1 92 154 6 93 140.1 23 177 134 134.1 128 24.1 45
#> 12.43 22.92 12.63 15.64 10.33 12.68 16.92 12.53 17.81 17.81 20.35 23.89 17.42
#> 43 68 99 108 92.1 187.1 100 107 81 179 61 179.1 184
#> 12.10 20.62 21.19 18.29 22.92 9.92 16.07 11.18 14.06 18.63 10.12 18.63 17.77
#> 42.2 29 180 150.1 164 105 125 188.1 52 91 63 57 79.1
#> 12.43 15.45 14.82 20.33 23.60 19.75 15.65 16.16 10.42 5.33 22.77 14.46 16.23
#> 14 79.2 36 154.1 85 171 57.1 5 136.1 168 181 177.1 184.1
#> 12.89 16.23 21.19 12.63 16.44 16.57 14.46 16.43 21.83 23.72 16.46 12.53 17.77
#> 49 58 37 145 170 100.1 140.2 134.2 179.2 69 93.1 70 63.1
#> 12.19 19.34 12.52 10.07 19.54 16.07 12.68 17.81 18.63 23.23 10.33 7.38 22.77
#> 68.1 13 37.1 177.2 183 133 79.3 123 96.1 197 66 139 76
#> 20.62 14.34 12.52 12.53 9.24 14.65 16.23 13.00 14.54 21.60 22.13 21.49 19.22
#> 43.1 78.1 78.2 32 167 190 167.1 61.1 154.2 66.1 84 20 135
#> 12.10 23.88 23.88 20.90 15.55 20.81 15.55 10.12 12.63 22.13 24.00 24.00 24.00
#> 48 20.1 131 3 135.1 200 64 21 47 162 131.1 44 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 172 1 9 17 31 1.1 176 65 98 71 160 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 148 72 38.1 75 173 109 196 21.1 44.1 119 122 148.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 48.1 19 84.1 103 156 176.1 12.1 142 118 22 132 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 9.1 142.1 9.2 22.1 33.1 161 22.2 137 191 196.1 3.1 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.2 178 74 47.1 131.2 71.1 191.1 104 161.1 122.1 67 65.1 67.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 54 109.1 172.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[58]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009257411 0.297747039 0.546304367
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.60021128 0.02854102 0.11885744
#> grade_iii, Cure model
#> 1.12965580
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 59 10.16 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 14 12.89 1 21 0 0
#> 127 3.53 1 62 0 1
#> 133 14.65 1 57 0 0
#> 125 15.65 1 67 1 0
#> 136 21.83 1 43 0 1
#> 96 14.54 1 33 0 1
#> 110 17.56 1 65 0 1
#> 42 12.43 1 49 0 1
#> 25 6.32 1 34 1 0
#> 139 21.49 1 63 1 0
#> 30.1 17.43 1 78 0 0
#> 57 14.46 1 45 0 1
#> 42.1 12.43 1 49 0 1
#> 57.1 14.46 1 45 0 1
#> 108 18.29 1 39 0 1
#> 18 15.21 1 49 1 0
#> 158 20.14 1 74 1 0
#> 78 23.88 1 43 0 0
#> 100 16.07 1 60 0 0
#> 81 14.06 1 34 0 0
#> 30.2 17.43 1 78 0 0
#> 13 14.34 1 54 0 1
#> 70 7.38 1 30 1 0
#> 57.2 14.46 1 45 0 1
#> 190 20.81 1 42 1 0
#> 39 15.59 1 37 0 1
#> 195 11.76 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 26 15.77 1 49 0 1
#> 157 15.10 1 47 0 0
#> 164 23.60 1 76 0 1
#> 155 13.08 1 26 0 0
#> 32 20.90 1 37 1 0
#> 29 15.45 1 68 1 0
#> 108.1 18.29 1 39 0 1
#> 59.1 10.16 1 NA 1 0
#> 171 16.57 1 41 0 1
#> 153 21.33 1 55 1 0
#> 30.3 17.43 1 78 0 0
#> 108.2 18.29 1 39 0 1
#> 195.1 11.76 1 NA 1 0
#> 59.2 10.16 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 192 16.44 1 31 1 0
#> 78.1 23.88 1 43 0 0
#> 99 21.19 1 38 0 1
#> 26.1 15.77 1 49 0 1
#> 123 13.00 1 44 1 0
#> 159 10.55 1 50 0 1
#> 107 11.18 1 54 1 0
#> 127.1 3.53 1 62 0 1
#> 181 16.46 1 45 0 1
#> 166 19.98 1 48 0 0
#> 127.2 3.53 1 62 0 1
#> 192.1 16.44 1 31 1 0
#> 187 9.92 1 39 1 0
#> 168 23.72 1 70 0 0
#> 129 23.41 1 53 1 0
#> 177 12.53 1 75 0 0
#> 140 12.68 1 59 1 0
#> 179 18.63 1 42 0 0
#> 190.1 20.81 1 42 1 0
#> 105 19.75 1 60 0 0
#> 130 16.47 1 53 0 1
#> 97 19.14 1 65 0 1
#> 168.1 23.72 1 70 0 0
#> 30.4 17.43 1 78 0 0
#> 51 18.23 1 83 0 1
#> 180 14.82 1 37 0 0
#> 78.2 23.88 1 43 0 0
#> 154 12.63 1 20 1 0
#> 77 7.27 1 67 0 1
#> 130.1 16.47 1 53 0 1
#> 51.1 18.23 1 83 0 1
#> 97.1 19.14 1 65 0 1
#> 130.2 16.47 1 53 0 1
#> 158.1 20.14 1 74 1 0
#> 197 21.60 1 69 1 0
#> 159.1 10.55 1 50 0 1
#> 197.1 21.60 1 69 1 0
#> 145 10.07 1 65 1 0
#> 195.2 11.76 1 NA 1 0
#> 181.1 16.46 1 45 0 1
#> 199 19.81 1 NA 0 1
#> 105.1 19.75 1 60 0 0
#> 96.1 14.54 1 33 0 1
#> 188 16.16 1 46 0 1
#> 129.1 23.41 1 53 1 0
#> 89 11.44 1 NA 0 0
#> 128 20.35 1 35 0 1
#> 91 5.33 1 61 0 1
#> 145.1 10.07 1 65 1 0
#> 91.1 5.33 1 61 0 1
#> 145.2 10.07 1 65 1 0
#> 117 17.46 1 26 0 1
#> 149 8.37 1 33 1 0
#> 96.2 14.54 1 33 0 1
#> 32.1 20.90 1 37 1 0
#> 40 18.00 1 28 1 0
#> 96.3 14.54 1 33 0 1
#> 180.1 14.82 1 37 0 0
#> 88 18.37 1 47 0 0
#> 56 12.21 1 60 0 0
#> 177.1 12.53 1 75 0 0
#> 164.1 23.60 1 76 0 1
#> 101 9.97 1 10 0 1
#> 192.2 16.44 1 31 1 0
#> 125.1 15.65 1 67 1 0
#> 51.2 18.23 1 83 0 1
#> 133.1 14.65 1 57 0 0
#> 3 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 53 24.00 0 32 0 1
#> 126 24.00 0 48 0 0
#> 83 24.00 0 6 0 0
#> 152 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 20 24.00 0 46 1 0
#> 135 24.00 0 58 1 0
#> 71 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#> 7 24.00 0 37 1 0
#> 120 24.00 0 68 0 1
#> 74 24.00 0 43 0 1
#> 19 24.00 0 57 0 1
#> 28 24.00 0 67 1 0
#> 87 24.00 0 27 0 0
#> 94 24.00 0 51 0 1
#> 156 24.00 0 50 1 0
#> 2 24.00 0 9 0 0
#> 1 24.00 0 23 1 0
#> 7.1 24.00 0 37 1 0
#> 27 24.00 0 63 1 0
#> 174 24.00 0 49 1 0
#> 131 24.00 0 66 0 0
#> 67 24.00 0 25 0 0
#> 48 24.00 0 31 1 0
#> 152.1 24.00 0 36 0 1
#> 138 24.00 0 44 1 0
#> 141 24.00 0 44 1 0
#> 71.1 24.00 0 51 0 0
#> 87.1 24.00 0 27 0 0
#> 98 24.00 0 34 1 0
#> 120.1 24.00 0 68 0 1
#> 186 24.00 0 45 1 0
#> 182 24.00 0 35 0 0
#> 186.1 24.00 0 45 1 0
#> 33 24.00 0 53 0 0
#> 87.2 24.00 0 27 0 0
#> 3.1 24.00 0 31 1 0
#> 182.1 24.00 0 35 0 0
#> 172 24.00 0 41 0 0
#> 64 24.00 0 43 0 0
#> 54 24.00 0 53 1 0
#> 163 24.00 0 66 0 0
#> 65 24.00 0 57 1 0
#> 48.1 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 148 24.00 0 61 1 0
#> 64.1 24.00 0 43 0 0
#> 186.2 24.00 0 45 1 0
#> 144 24.00 0 28 0 1
#> 67.1 24.00 0 25 0 0
#> 186.3 24.00 0 45 1 0
#> 103 24.00 0 56 1 0
#> 122.1 24.00 0 66 0 0
#> 126.1 24.00 0 48 0 0
#> 191 24.00 0 60 0 1
#> 118 24.00 0 44 1 0
#> 182.2 24.00 0 35 0 0
#> 104 24.00 0 50 1 0
#> 21 24.00 0 47 0 0
#> 112 24.00 0 61 0 0
#> 82 24.00 0 34 0 0
#> 98.1 24.00 0 34 1 0
#> 98.2 24.00 0 34 1 0
#> 71.2 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 198 24.00 0 66 0 1
#> 84 24.00 0 39 0 1
#> 84.1 24.00 0 39 0 1
#> 98.3 24.00 0 34 1 0
#> 83.1 24.00 0 6 0 0
#> 147 24.00 0 76 1 0
#> 11 24.00 0 42 0 1
#> 116 24.00 0 58 0 1
#> 126.2 24.00 0 48 0 0
#> 87.3 24.00 0 27 0 0
#> 27.1 24.00 0 63 1 0
#> 112.1 24.00 0 61 0 0
#> 98.4 24.00 0 34 1 0
#> 126.3 24.00 0 48 0 0
#> 54.1 24.00 0 53 1 0
#> 122.2 24.00 0 66 0 0
#> 72 24.00 0 40 0 1
#> 95 24.00 0 68 0 1
#> 38 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.60 NA NA NA
#> 2 age, Cure model 0.0285 NA NA NA
#> 3 grade_ii, Cure model 0.119 NA NA NA
#> 4 grade_iii, Cure model 1.13 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00926 NA NA NA
#> 2 grade_ii, Survival model 0.298 NA NA NA
#> 3 grade_iii, Survival model 0.546 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.60021 0.02854 0.11886 1.12966
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 244.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.60021128 0.02854102 0.11885744 1.12965580
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009257411 0.297747039 0.546304367
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.337442083 0.734439004 0.968177579 0.600178139 0.517640001 0.056574077
#> [7] 0.621313607 0.308183353 0.787063696 0.936150927 0.080615734 0.337442083
#> [13] 0.662123717 0.787063696 0.662123717 0.232766813 0.558603951 0.149377710
#> [19] 0.003197491 0.487223009 0.703140390 0.337442083 0.692775867 0.914737827
#> [25] 0.662123717 0.123707598 0.538040548 0.327747562 0.497458779 0.568940408
#> [31] 0.027240148 0.713546335 0.106892180 0.548295029 0.232766813 0.386645542
#> [37] 0.089320409 0.337442083 0.232766813 0.298364411 0.447206320 0.003197491
#> [43] 0.098190372 0.497458779 0.723984846 0.829508951 0.818813832 0.968177579
#> [49] 0.427049031 0.166807738 0.968177579 0.447206320 0.893329473 0.014172632
#> [55] 0.041429007 0.765928228 0.744919521 0.213218406 0.123707598 0.175939103
#> [61] 0.396978839 0.194529956 0.014172632 0.337442083 0.260404069 0.579343548
#> [67] 0.003197491 0.755432577 0.925439962 0.396978839 0.260404069 0.194529956
#> [73] 0.396978839 0.149377710 0.064553619 0.829508951 0.064553619 0.850714054
#> [79] 0.427049031 0.175939103 0.621313607 0.477078075 0.041429007 0.140727699
#> [85] 0.946863960 0.850714054 0.946863960 0.850714054 0.318019218 0.904033160
#> [91] 0.621313607 0.106892180 0.288640393 0.621313607 0.579343548 0.222916993
#> [97] 0.808144221 0.765928228 0.027240148 0.882633647 0.447206320 0.517640001
#> [103] 0.260404069 0.600178139 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 30 14 127 133 125 136 96 110 42 25 139 30.1 57
#> 17.43 12.89 3.53 14.65 15.65 21.83 14.54 17.56 12.43 6.32 21.49 17.43 14.46
#> 42.1 57.1 108 18 158 78 100 81 30.2 13 70 57.2 190
#> 12.43 14.46 18.29 15.21 20.14 23.88 16.07 14.06 17.43 14.34 7.38 14.46 20.81
#> 39 111 26 157 164 155 32 29 108.1 171 153 30.3 108.2
#> 15.59 17.45 15.77 15.10 23.60 13.08 20.90 15.45 18.29 16.57 21.33 17.43 18.29
#> 184 192 78.1 99 26.1 123 159 107 127.1 181 166 127.2 192.1
#> 17.77 16.44 23.88 21.19 15.77 13.00 10.55 11.18 3.53 16.46 19.98 3.53 16.44
#> 187 168 129 177 140 179 190.1 105 130 97 168.1 30.4 51
#> 9.92 23.72 23.41 12.53 12.68 18.63 20.81 19.75 16.47 19.14 23.72 17.43 18.23
#> 180 78.2 154 77 130.1 51.1 97.1 130.2 158.1 197 159.1 197.1 145
#> 14.82 23.88 12.63 7.27 16.47 18.23 19.14 16.47 20.14 21.60 10.55 21.60 10.07
#> 181.1 105.1 96.1 188 129.1 128 91 145.1 91.1 145.2 117 149 96.2
#> 16.46 19.75 14.54 16.16 23.41 20.35 5.33 10.07 5.33 10.07 17.46 8.37 14.54
#> 32.1 40 96.3 180.1 88 56 177.1 164.1 101 192.2 125.1 51.2 133.1
#> 20.90 18.00 14.54 14.82 18.37 12.21 12.53 23.60 9.97 16.44 15.65 18.23 14.65
#> 3 122 165 53 126 83 152 132 20 135 71 196 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 74 19 28 87 94 156 2 1 7.1 27 174 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 48 152.1 138 141 71.1 87.1 98 120.1 186 182 186.1 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.2 3.1 182.1 172 64 54 163 65 48.1 178 148 64.1 186.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 67.1 186.3 103 122.1 126.1 191 118 182.2 104 21 112 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.1 98.2 71.2 47 198 84 84.1 98.3 83.1 147 11 116 126.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.3 27.1 112.1 98.4 126.3 54.1 122.2 72 95 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[59]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005043522 0.626585431 0.215449229
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.634767502 0.008465019 0.236196471
#> grade_iii, Cure model
#> 0.936216476
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 179 18.63 1 42 0 0
#> 42 12.43 1 49 0 1
#> 93 10.33 1 52 0 1
#> 40 18.00 1 28 1 0
#> 166 19.98 1 48 0 0
#> 97 19.14 1 65 0 1
#> 51 18.23 1 83 0 1
#> 23 16.92 1 61 0 0
#> 89 11.44 1 NA 0 0
#> 175 21.91 1 43 0 0
#> 189 10.51 1 NA 1 0
#> 51.1 18.23 1 83 0 1
#> 93.1 10.33 1 52 0 1
#> 8 18.43 1 32 0 0
#> 89.1 11.44 1 NA 0 0
#> 40.1 18.00 1 28 1 0
#> 81 14.06 1 34 0 0
#> 37 12.52 1 57 1 0
#> 37.1 12.52 1 57 1 0
#> 39 15.59 1 37 0 1
#> 133 14.65 1 57 0 0
#> 153 21.33 1 55 1 0
#> 85 16.44 1 36 0 0
#> 61 10.12 1 36 0 1
#> 29 15.45 1 68 1 0
#> 177 12.53 1 75 0 0
#> 184 17.77 1 38 0 0
#> 192 16.44 1 31 1 0
#> 57 14.46 1 45 0 1
#> 39.1 15.59 1 37 0 1
#> 16 8.71 1 71 0 1
#> 180 14.82 1 37 0 0
#> 184.1 17.77 1 38 0 0
#> 77 7.27 1 67 0 1
#> 195 11.76 1 NA 1 0
#> 189.1 10.51 1 NA 1 0
#> 133.1 14.65 1 57 0 0
#> 81.1 14.06 1 34 0 0
#> 15 22.68 1 48 0 0
#> 188 16.16 1 46 0 1
#> 45 17.42 1 54 0 1
#> 4 17.64 1 NA 0 1
#> 15.1 22.68 1 48 0 0
#> 96 14.54 1 33 0 1
#> 169 22.41 1 46 0 0
#> 195.1 11.76 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 167 15.55 1 56 1 0
#> 36 21.19 1 48 0 1
#> 81.2 14.06 1 34 0 0
#> 183 9.24 1 67 1 0
#> 92.1 22.92 1 47 0 1
#> 56 12.21 1 60 0 0
#> 50 10.02 1 NA 1 0
#> 39.2 15.59 1 37 0 1
#> 159 10.55 1 50 0 1
#> 175.1 21.91 1 43 0 0
#> 107 11.18 1 54 1 0
#> 145 10.07 1 65 1 0
#> 81.3 14.06 1 34 0 0
#> 187 9.92 1 39 1 0
#> 61.1 10.12 1 36 0 1
#> 128 20.35 1 35 0 1
#> 114 13.68 1 NA 0 0
#> 100 16.07 1 60 0 0
#> 130 16.47 1 53 0 1
#> 139 21.49 1 63 1 0
#> 37.2 12.52 1 57 1 0
#> 81.4 14.06 1 34 0 0
#> 89.2 11.44 1 NA 0 0
#> 114.1 13.68 1 NA 0 0
#> 81.5 14.06 1 34 0 0
#> 89.3 11.44 1 NA 0 0
#> 133.2 14.65 1 57 0 0
#> 129 23.41 1 53 1 0
#> 45.1 17.42 1 54 0 1
#> 140 12.68 1 59 1 0
#> 92.2 22.92 1 47 0 1
#> 187.1 9.92 1 39 1 0
#> 130.1 16.47 1 53 0 1
#> 23.1 16.92 1 61 0 0
#> 5 16.43 1 51 0 1
#> 78 23.88 1 43 0 0
#> 15.2 22.68 1 48 0 0
#> 97.1 19.14 1 65 0 1
#> 114.2 13.68 1 NA 0 0
#> 92.3 22.92 1 47 0 1
#> 51.2 18.23 1 83 0 1
#> 111 17.45 1 47 0 1
#> 181 16.46 1 45 0 1
#> 61.2 10.12 1 36 0 1
#> 25 6.32 1 34 1 0
#> 114.3 13.68 1 NA 0 0
#> 59 10.16 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 51.3 18.23 1 83 0 1
#> 171 16.57 1 41 0 1
#> 190 20.81 1 42 1 0
#> 107.1 11.18 1 54 1 0
#> 8.1 18.43 1 32 0 0
#> 14 12.89 1 21 0 0
#> 108 18.29 1 39 0 1
#> 167.1 15.55 1 56 1 0
#> 70 7.38 1 30 1 0
#> 107.2 11.18 1 54 1 0
#> 105 19.75 1 60 0 0
#> 154 12.63 1 20 1 0
#> 25.1 6.32 1 34 1 0
#> 110 17.56 1 65 0 1
#> 150 20.33 1 48 0 0
#> 96.1 14.54 1 33 0 1
#> 57.1 14.46 1 45 0 1
#> 33 24.00 0 53 0 0
#> 75 24.00 0 21 1 0
#> 193 24.00 0 45 0 1
#> 102 24.00 0 49 0 0
#> 82 24.00 0 34 0 0
#> 71 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 1 24.00 0 23 1 0
#> 172 24.00 0 41 0 0
#> 34 24.00 0 36 0 0
#> 143 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 132 24.00 0 55 0 0
#> 142 24.00 0 53 0 0
#> 98 24.00 0 34 1 0
#> 132.1 24.00 0 55 0 0
#> 176 24.00 0 43 0 1
#> 200 24.00 0 64 0 0
#> 132.2 24.00 0 55 0 0
#> 174 24.00 0 49 1 0
#> 62 24.00 0 71 0 0
#> 120 24.00 0 68 0 1
#> 33.1 24.00 0 53 0 0
#> 65 24.00 0 57 1 0
#> 173 24.00 0 19 0 1
#> 116 24.00 0 58 0 1
#> 103 24.00 0 56 1 0
#> 95 24.00 0 68 0 1
#> 83 24.00 0 6 0 0
#> 74 24.00 0 43 0 1
#> 73 24.00 0 NA 0 1
#> 174.1 24.00 0 49 1 0
#> 131 24.00 0 66 0 0
#> 162 24.00 0 51 0 0
#> 148 24.00 0 61 1 0
#> 196 24.00 0 19 0 0
#> 21 24.00 0 47 0 0
#> 186 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 144 24.00 0 28 0 1
#> 83.1 24.00 0 6 0 0
#> 94 24.00 0 51 0 1
#> 35 24.00 0 51 0 0
#> 198 24.00 0 66 0 1
#> 11 24.00 0 42 0 1
#> 53 24.00 0 32 0 1
#> 186.1 24.00 0 45 1 0
#> 74.1 24.00 0 43 0 1
#> 102.1 24.00 0 49 0 0
#> 178 24.00 0 52 1 0
#> 11.1 24.00 0 42 0 1
#> 7.1 24.00 0 37 1 0
#> 7.2 24.00 0 37 1 0
#> 182 24.00 0 35 0 0
#> 132.3 24.00 0 55 0 0
#> 1.1 24.00 0 23 1 0
#> 11.2 24.00 0 42 0 1
#> 161 24.00 0 45 0 0
#> 62.1 24.00 0 71 0 0
#> 84 24.00 0 39 0 1
#> 186.2 24.00 0 45 1 0
#> 103.1 24.00 0 56 1 0
#> 71.1 24.00 0 51 0 0
#> 148.1 24.00 0 61 1 0
#> 116.1 24.00 0 58 0 1
#> 1.2 24.00 0 23 1 0
#> 151 24.00 0 42 0 0
#> 162.1 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 67 24.00 0 25 0 0
#> 185 24.00 0 44 1 0
#> 103.2 24.00 0 56 1 0
#> 141 24.00 0 44 1 0
#> 82.1 24.00 0 34 0 0
#> 109 24.00 0 48 0 0
#> 67.1 24.00 0 25 0 0
#> 103.3 24.00 0 56 1 0
#> 46 24.00 0 71 0 0
#> 161.1 24.00 0 45 0 0
#> 126 24.00 0 48 0 0
#> 44 24.00 0 56 0 0
#> 182.1 24.00 0 35 0 0
#> 80 24.00 0 41 0 0
#> 47 24.00 0 38 0 1
#> 147 24.00 0 76 1 0
#> 62.2 24.00 0 71 0 0
#> 28 24.00 0 67 1 0
#> 73.1 24.00 0 NA 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.635 NA NA NA
#> 2 age, Cure model 0.00847 NA NA NA
#> 3 grade_ii, Cure model 0.236 NA NA NA
#> 4 grade_iii, Cure model 0.936 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00504 NA NA NA
#> 2 grade_ii, Survival model 0.627 NA NA NA
#> 3 grade_iii, Survival model 0.215 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.634768 0.008465 0.236196 0.936216
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 253
#> Residual Deviance: 244.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.634767502 0.008465019 0.236196471 0.936216476
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005043522 0.626585431 0.215449229
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.225023553 0.797501182 0.858991287 0.307328618 0.184550751 0.204868211
#> [7] 0.266562417 0.400210631 0.103174691 0.266562417 0.858991287 0.235428709
#> [13] 0.307328618 0.662615550 0.766734877 0.766734877 0.516726110 0.589606101
#> [19] 0.134455420 0.463873044 0.879415916 0.568765524 0.756165640 0.327568920
#> [25] 0.463873044 0.641689046 0.516726110 0.950191966 0.579169853 0.327568920
#> [31] 0.970272572 0.589606101 0.662615550 0.065120294 0.495445082 0.379395557
#> [37] 0.065120294 0.620770408 0.092656034 0.033988678 0.548023928 0.144644757
#> [43] 0.662615550 0.940133900 0.033988678 0.807895622 0.516726110 0.848728773
#> [49] 0.103174691 0.818325102 0.909838074 0.662615550 0.920053872 0.879415916
#> [55] 0.164727578 0.506056383 0.432002826 0.123933399 0.766734877 0.662615550
#> [61] 0.662615550 0.589606101 0.021738090 0.379395557 0.735016092 0.033988678
#> [67] 0.920053872 0.432002826 0.400210631 0.484837518 0.006276934 0.065120294
#> [73] 0.204868211 0.033988678 0.266562417 0.358448652 0.453163378 0.879415916
#> [79] 0.980292852 0.368873740 0.266562417 0.421316603 0.154853290 0.818325102
#> [85] 0.235428709 0.724329264 0.256045719 0.548023928 0.960264205 0.818325102
#> [91] 0.194640217 0.745642729 0.980292852 0.348030058 0.174578611 0.620770408
#> [97] 0.641689046 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 179 42 93 40 166 97 51 23 175 51.1 93.1 8 40.1
#> 18.63 12.43 10.33 18.00 19.98 19.14 18.23 16.92 21.91 18.23 10.33 18.43 18.00
#> 81 37 37.1 39 133 153 85 61 29 177 184 192 57
#> 14.06 12.52 12.52 15.59 14.65 21.33 16.44 10.12 15.45 12.53 17.77 16.44 14.46
#> 39.1 16 180 184.1 77 133.1 81.1 15 188 45 15.1 96 169
#> 15.59 8.71 14.82 17.77 7.27 14.65 14.06 22.68 16.16 17.42 22.68 14.54 22.41
#> 92 167 36 81.2 183 92.1 56 39.2 159 175.1 107 145 81.3
#> 22.92 15.55 21.19 14.06 9.24 22.92 12.21 15.59 10.55 21.91 11.18 10.07 14.06
#> 187 61.1 128 100 130 139 37.2 81.4 81.5 133.2 129 45.1 140
#> 9.92 10.12 20.35 16.07 16.47 21.49 12.52 14.06 14.06 14.65 23.41 17.42 12.68
#> 92.2 187.1 130.1 23.1 5 78 15.2 97.1 92.3 51.2 111 181 61.2
#> 22.92 9.92 16.47 16.92 16.43 23.88 22.68 19.14 22.92 18.23 17.45 16.46 10.12
#> 25 30 51.3 171 190 107.1 8.1 14 108 167.1 70 107.2 105
#> 6.32 17.43 18.23 16.57 20.81 11.18 18.43 12.89 18.29 15.55 7.38 11.18 19.75
#> 154 25.1 110 150 96.1 57.1 33 75 193 102 82 71 87
#> 12.63 6.32 17.56 20.33 14.54 14.46 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 172 34 143 7 132 142 98 132.1 176 200 132.2 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 120 33.1 65 173 116 103 95 83 74 174.1 131 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 196 21 186 163 144 83.1 94 35 198 11 53 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.1 102.1 178 11.1 7.1 7.2 182 132.3 1.1 11.2 161 62.1 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.2 103.1 71.1 148.1 116.1 1.2 151 162.1 19 67 185 103.2 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.1 109 67.1 103.3 46 161.1 126 44 182.1 80 47 147 62.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[60]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01719782 1.02510041 0.27890720
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.518485385 0.004944777 0.493839955
#> grade_iii, Cure model
#> 0.808381353
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 133 14.65 1 57 0 0
#> 26 15.77 1 49 0 1
#> 78 23.88 1 43 0 0
#> 30 17.43 1 78 0 0
#> 125 15.65 1 67 1 0
#> 58 19.34 1 39 0 0
#> 150 20.33 1 48 0 0
#> 189 10.51 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 199 19.81 1 NA 0 1
#> 159 10.55 1 50 0 1
#> 79 16.23 1 54 1 0
#> 149 8.37 1 33 1 0
#> 77 7.27 1 67 0 1
#> 92 22.92 1 47 0 1
#> 166 19.98 1 48 0 0
#> 26.1 15.77 1 49 0 1
#> 93 10.33 1 52 0 1
#> 92.1 22.92 1 47 0 1
#> 88 18.37 1 47 0 0
#> 88.1 18.37 1 47 0 0
#> 55 19.34 1 69 0 1
#> 51 18.23 1 83 0 1
#> 5 16.43 1 51 0 1
#> 133.1 14.65 1 57 0 0
#> 58.1 19.34 1 39 0 0
#> 68 20.62 1 44 0 0
#> 57 14.46 1 45 0 1
#> 91 5.33 1 61 0 1
#> 180 14.82 1 37 0 0
#> 63 22.77 1 31 1 0
#> 113 22.86 1 34 0 0
#> 69 23.23 1 25 0 1
#> 187 9.92 1 39 1 0
#> 79.1 16.23 1 54 1 0
#> 5.1 16.43 1 51 0 1
#> 79.2 16.23 1 54 1 0
#> 36 21.19 1 48 0 1
#> 125.1 15.65 1 67 1 0
#> 77.1 7.27 1 67 0 1
#> 90 20.94 1 50 0 1
#> 179.1 18.63 1 42 0 0
#> 111 17.45 1 47 0 1
#> 43 12.10 1 61 0 1
#> 59 10.16 1 NA 1 0
#> 55.1 19.34 1 69 0 1
#> 157 15.10 1 47 0 0
#> 166.1 19.98 1 48 0 0
#> 171 16.57 1 41 0 1
#> 50 10.02 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 43.1 12.10 1 61 0 1
#> 194 22.40 1 38 0 1
#> 155 13.08 1 26 0 0
#> 168 23.72 1 70 0 0
#> 145 10.07 1 65 1 0
#> 89 11.44 1 NA 0 0
#> 134 17.81 1 47 1 0
#> 23 16.92 1 61 0 0
#> 108 18.29 1 39 0 1
#> 117 17.46 1 26 0 1
#> 24 23.89 1 38 0 0
#> 140 12.68 1 59 1 0
#> 105 19.75 1 60 0 0
#> 153 21.33 1 55 1 0
#> 92.2 22.92 1 47 0 1
#> 111.1 17.45 1 47 0 1
#> 199.1 19.81 1 NA 0 1
#> 167 15.55 1 56 1 0
#> 99 21.19 1 38 0 1
#> 55.2 19.34 1 69 0 1
#> 100 16.07 1 60 0 0
#> 14 12.89 1 21 0 0
#> 183 9.24 1 67 1 0
#> 159.1 10.55 1 50 0 1
#> 167.1 15.55 1 56 1 0
#> 170 19.54 1 43 0 1
#> 97 19.14 1 65 0 1
#> 50.1 10.02 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 13 14.34 1 54 0 1
#> 93.1 10.33 1 52 0 1
#> 149.1 8.37 1 33 1 0
#> 37 12.52 1 57 1 0
#> 154 12.63 1 20 1 0
#> 127.1 3.53 1 62 0 1
#> 192 16.44 1 31 1 0
#> 36.1 21.19 1 48 0 1
#> 41 18.02 1 40 1 0
#> 123 13.00 1 44 1 0
#> 5.2 16.43 1 51 0 1
#> 117.1 17.46 1 26 0 1
#> 10 10.53 1 34 0 0
#> 69.1 23.23 1 25 0 1
#> 70 7.38 1 30 1 0
#> 194.1 22.40 1 38 0 1
#> 8 18.43 1 32 0 0
#> 36.2 21.19 1 48 0 1
#> 4 17.64 1 NA 0 1
#> 89.1 11.44 1 NA 0 0
#> 149.2 8.37 1 33 1 0
#> 58.2 19.34 1 39 0 0
#> 128 20.35 1 35 0 1
#> 37.1 12.52 1 57 1 0
#> 5.3 16.43 1 51 0 1
#> 192.1 16.44 1 31 1 0
#> 70.1 7.38 1 30 1 0
#> 76 19.22 1 54 0 1
#> 59.1 10.16 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 63.1 22.77 1 31 1 0
#> 188 16.16 1 46 0 1
#> 54 24.00 0 53 1 0
#> 163 24.00 0 66 0 0
#> 3 24.00 0 31 1 0
#> 54.1 24.00 0 53 1 0
#> 1 24.00 0 23 1 0
#> 163.1 24.00 0 66 0 0
#> 163.2 24.00 0 66 0 0
#> 200 24.00 0 64 0 0
#> 74 24.00 0 43 0 1
#> 121 24.00 0 57 1 0
#> 118 24.00 0 44 1 0
#> 53 24.00 0 32 0 1
#> 98 24.00 0 34 1 0
#> 182 24.00 0 35 0 0
#> 116 24.00 0 58 0 1
#> 53.1 24.00 0 32 0 1
#> 64 24.00 0 43 0 0
#> 3.1 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 141 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 156 24.00 0 50 1 0
#> 47 24.00 0 38 0 1
#> 138 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 135 24.00 0 58 1 0
#> 31 24.00 0 36 0 1
#> 17 24.00 0 38 0 1
#> 118.1 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 144 24.00 0 28 0 1
#> 182.1 24.00 0 35 0 0
#> 44 24.00 0 56 0 0
#> 33 24.00 0 53 0 0
#> 182.2 24.00 0 35 0 0
#> 143 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 95 24.00 0 68 0 1
#> 176 24.00 0 43 0 1
#> 71 24.00 0 51 0 0
#> 200.1 24.00 0 64 0 0
#> 84 24.00 0 39 0 1
#> 38 24.00 0 31 1 0
#> 120.1 24.00 0 68 0 1
#> 1.1 24.00 0 23 1 0
#> 74.1 24.00 0 43 0 1
#> 137 24.00 0 45 1 0
#> 112 24.00 0 61 0 0
#> 191.1 24.00 0 60 0 1
#> 65 24.00 0 57 1 0
#> 72 24.00 0 40 0 1
#> 74.2 24.00 0 43 0 1
#> 102 24.00 0 49 0 0
#> 20 24.00 0 46 1 0
#> 135.1 24.00 0 58 1 0
#> 83 24.00 0 6 0 0
#> 71.1 24.00 0 51 0 0
#> 174 24.00 0 49 1 0
#> 131 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 151.1 24.00 0 42 0 0
#> 82 24.00 0 34 0 0
#> 119 24.00 0 17 0 0
#> 137.1 24.00 0 45 1 0
#> 82.1 24.00 0 34 0 0
#> 131.1 24.00 0 66 0 0
#> 151.2 24.00 0 42 0 0
#> 35 24.00 0 51 0 0
#> 102.1 24.00 0 49 0 0
#> 34 24.00 0 36 0 0
#> 115 24.00 0 NA 1 0
#> 172 24.00 0 41 0 0
#> 31.1 24.00 0 36 0 1
#> 103 24.00 0 56 1 0
#> 53.2 24.00 0 32 0 1
#> 71.2 24.00 0 51 0 0
#> 46 24.00 0 71 0 0
#> 95.1 24.00 0 68 0 1
#> 198.1 24.00 0 66 0 1
#> 151.3 24.00 0 42 0 0
#> 17.1 24.00 0 38 0 1
#> 98.1 24.00 0 34 1 0
#> 198.2 24.00 0 66 0 1
#> 176.1 24.00 0 43 0 1
#> 47.1 24.00 0 38 0 1
#> 196 24.00 0 19 0 0
#> 73 24.00 0 NA 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.518 NA NA NA
#> 2 age, Cure model 0.00494 NA NA NA
#> 3 grade_ii, Cure model 0.494 NA NA NA
#> 4 grade_iii, Cure model 0.808 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0172 NA NA NA
#> 2 grade_ii, Survival model 1.03 NA NA NA
#> 3 grade_iii, Survival model 0.279 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.518485 0.004945 0.493840 0.808381
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 252.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.518485385 0.004944777 0.493839955 0.808381353
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01719782 1.02510041 0.27890720
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9012273 0.8700363 0.2237254 0.8022782 0.8784961 0.6628277 0.6174937
#> [8] 0.7206285 0.9459287 0.8481800 0.9702977 0.9841270 0.3917541 0.6270068
#> [15] 0.8700363 0.9552968 0.3917541 0.7412195 0.7412195 0.6628277 0.7611645
#> [22] 0.8288666 0.9012273 0.6628277 0.5978599 0.9085129 0.9921609 0.8975273
#> [29] 0.4751222 0.4541081 0.3287844 0.9644421 0.8481800 0.8288666 0.8481800
#> [36] 0.5468423 0.8784961 0.9841270 0.5877410 0.7206285 0.7910651 0.9395925
#> [43] 0.6628277 0.8938136 0.6270068 0.8132431 0.9894998 0.9395925 0.5061585
#> [50] 0.9157253 0.2869620 0.9614386 0.7736487 0.8077952 0.7545583 0.7795306
#> [57] 0.1329810 0.9263290 0.6451863 0.5345170 0.3917541 0.7910651 0.8863632
#> [64] 0.5468423 0.6628277 0.8657087 0.9228209 0.9674045 0.9459287 0.8863632
#> [71] 0.6541122 0.7135838 0.9948024 0.9121358 0.9552968 0.9702977 0.9331355
#> [78] 0.9297505 0.9948024 0.8186307 0.5468423 0.7675219 0.9193069 0.8288666
#> [85] 0.7795306 0.9521761 0.3287844 0.9786591 0.5061585 0.7343657 0.5468423
#> [92] 0.9702977 0.6628277 0.6077888 0.9331355 0.8288666 0.8186307 0.9786591
#> [99] 0.7063211 0.4751222 0.8613418 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 133 26 78 30 125 58 150 179 159 79 149 77 92
#> 14.65 15.77 23.88 17.43 15.65 19.34 20.33 18.63 10.55 16.23 8.37 7.27 22.92
#> 166 26.1 93 92.1 88 88.1 55 51 5 133.1 58.1 68 57
#> 19.98 15.77 10.33 22.92 18.37 18.37 19.34 18.23 16.43 14.65 19.34 20.62 14.46
#> 91 180 63 113 69 187 79.1 5.1 79.2 36 125.1 77.1 90
#> 5.33 14.82 22.77 22.86 23.23 9.92 16.23 16.43 16.23 21.19 15.65 7.27 20.94
#> 179.1 111 43 55.1 157 166.1 171 25 43.1 194 155 168 145
#> 18.63 17.45 12.10 19.34 15.10 19.98 16.57 6.32 12.10 22.40 13.08 23.72 10.07
#> 134 23 108 117 24 140 105 153 92.2 111.1 167 99 55.2
#> 17.81 16.92 18.29 17.46 23.89 12.68 19.75 21.33 22.92 17.45 15.55 21.19 19.34
#> 100 14 183 159.1 167.1 170 97 127 13 93.1 149.1 37 154
#> 16.07 12.89 9.24 10.55 15.55 19.54 19.14 3.53 14.34 10.33 8.37 12.52 12.63
#> 127.1 192 36.1 41 123 5.2 117.1 10 69.1 70 194.1 8 36.2
#> 3.53 16.44 21.19 18.02 13.00 16.43 17.46 10.53 23.23 7.38 22.40 18.43 21.19
#> 149.2 58.2 128 37.1 5.3 192.1 70.1 76 63.1 188 54 163 3
#> 8.37 19.34 20.35 12.52 16.43 16.44 7.38 19.22 22.77 16.16 24.00 24.00 24.00
#> 54.1 1 163.1 163.2 200 74 121 118 53 98 182 116 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 3.1 191 141 120 156 47 138 151 135 31 17 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 198 144 182.1 44 33 182.2 143 12 95 176 71 200.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 38 120.1 1.1 74.1 137 112 191.1 65 72 74.2 102 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 83 71.1 174 131 87 151.1 82 119 137.1 82.1 131.1 151.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 102.1 34 172 31.1 103 53.2 71.2 46 95.1 198.1 151.3 17.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.1 198.2 176.1 47.1 196
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[61]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.009336814 0.397820419 0.107024367
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.18716100 0.02623782 -0.24153106
#> grade_iii, Cure model
#> 0.64462794
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 52 10.42 1 52 0 1
#> 68 20.62 1 44 0 0
#> 59 10.16 1 NA 1 0
#> 56 12.21 1 60 0 0
#> 158 20.14 1 74 1 0
#> 184 17.77 1 38 0 0
#> 70 7.38 1 30 1 0
#> 97 19.14 1 65 0 1
#> 150 20.33 1 48 0 0
#> 16 8.71 1 71 0 1
#> 117 17.46 1 26 0 1
#> 159 10.55 1 50 0 1
#> 79 16.23 1 54 1 0
#> 150.1 20.33 1 48 0 0
#> 86 23.81 1 58 0 1
#> 63 22.77 1 31 1 0
#> 125 15.65 1 67 1 0
#> 183 9.24 1 67 1 0
#> 43 12.10 1 61 0 1
#> 15 22.68 1 48 0 0
#> 110 17.56 1 65 0 1
#> 179 18.63 1 42 0 0
#> 41 18.02 1 40 1 0
#> 13 14.34 1 54 0 1
#> 175 21.91 1 43 0 0
#> 6 15.64 1 39 0 0
#> 180 14.82 1 37 0 0
#> 90 20.94 1 50 0 1
#> 39 15.59 1 37 0 1
#> 177 12.53 1 75 0 0
#> 140 12.68 1 59 1 0
#> 69 23.23 1 25 0 1
#> 140.1 12.68 1 59 1 0
#> 66 22.13 1 53 0 0
#> 134 17.81 1 47 1 0
#> 25 6.32 1 34 1 0
#> 145 10.07 1 65 1 0
#> 159.1 10.55 1 50 0 1
#> 166 19.98 1 48 0 0
#> 180.1 14.82 1 37 0 0
#> 40 18.00 1 28 1 0
#> 86.1 23.81 1 58 0 1
#> 23 16.92 1 61 0 0
#> 23.1 16.92 1 61 0 0
#> 150.2 20.33 1 48 0 0
#> 50 10.02 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 16.1 8.71 1 71 0 1
#> 130 16.47 1 53 0 1
#> 107 11.18 1 54 1 0
#> 55 19.34 1 69 0 1
#> 88 18.37 1 47 0 0
#> 92 22.92 1 47 0 1
#> 37 12.52 1 57 1 0
#> 192 16.44 1 31 1 0
#> 100 16.07 1 60 0 0
#> 45 17.42 1 54 0 1
#> 184.1 17.77 1 38 0 0
#> 51 18.23 1 83 0 1
#> 123 13.00 1 44 1 0
#> 39.1 15.59 1 37 0 1
#> 125.1 15.65 1 67 1 0
#> 32 20.90 1 37 1 0
#> 90.1 20.94 1 50 0 1
#> 113 22.86 1 34 0 0
#> 6.1 15.64 1 39 0 0
#> 66.1 22.13 1 53 0 0
#> 85 16.44 1 36 0 0
#> 127 3.53 1 62 0 1
#> 140.2 12.68 1 59 1 0
#> 192.1 16.44 1 31 1 0
#> 129 23.41 1 53 1 0
#> 36 21.19 1 48 0 1
#> 85.1 16.44 1 36 0 0
#> 89 11.44 1 NA 0 0
#> 16.2 8.71 1 71 0 1
#> 127.1 3.53 1 62 0 1
#> 56.1 12.21 1 60 0 0
#> 76 19.22 1 54 0 1
#> 60 13.15 1 38 1 0
#> 55.1 19.34 1 69 0 1
#> 66.2 22.13 1 53 0 0
#> 8 18.43 1 32 0 0
#> 155 13.08 1 26 0 0
#> 110.1 17.56 1 65 0 1
#> 36.1 21.19 1 48 0 1
#> 23.2 16.92 1 61 0 0
#> 100.1 16.07 1 60 0 0
#> 56.2 12.21 1 60 0 0
#> 16.3 8.71 1 71 0 1
#> 105 19.75 1 60 0 0
#> 39.2 15.59 1 37 0 1
#> 90.2 20.94 1 50 0 1
#> 106 16.67 1 49 1 0
#> 30.1 17.43 1 78 0 0
#> 10 10.53 1 34 0 0
#> 42 12.43 1 49 0 1
#> 57 14.46 1 45 0 1
#> 88.1 18.37 1 47 0 0
#> 43.1 12.10 1 61 0 1
#> 169 22.41 1 46 0 0
#> 190 20.81 1 42 1 0
#> 130.1 16.47 1 53 0 1
#> 32.1 20.90 1 37 1 0
#> 170 19.54 1 43 0 1
#> 52.1 10.42 1 52 0 1
#> 57.1 14.46 1 45 0 1
#> 168 23.72 1 70 0 0
#> 4 17.64 1 NA 0 1
#> 60.1 13.15 1 38 1 0
#> 157 15.10 1 47 0 0
#> 52.2 10.42 1 52 0 1
#> 31 24.00 0 36 0 1
#> 7 24.00 0 37 1 0
#> 72 24.00 0 40 0 1
#> 118 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 44 24.00 0 56 0 0
#> 98 24.00 0 34 1 0
#> 31.1 24.00 0 36 0 1
#> 62 24.00 0 71 0 0
#> 67 24.00 0 25 0 0
#> 11 24.00 0 42 0 1
#> 191 24.00 0 60 0 1
#> 147 24.00 0 76 1 0
#> 152 24.00 0 36 0 1
#> 82 24.00 0 34 0 0
#> 62.1 24.00 0 71 0 0
#> 152.1 24.00 0 36 0 1
#> 148 24.00 0 61 1 0
#> 65 24.00 0 57 1 0
#> 151 24.00 0 42 0 0
#> 104 24.00 0 50 1 0
#> 142 24.00 0 53 0 0
#> 173 24.00 0 19 0 1
#> 144 24.00 0 28 0 1
#> 12 24.00 0 63 0 0
#> 48 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 11.1 24.00 0 42 0 1
#> 80 24.00 0 41 0 0
#> 173.1 24.00 0 19 0 1
#> 48.1 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 172 24.00 0 41 0 0
#> 121.1 24.00 0 57 1 0
#> 174 24.00 0 49 1 0
#> 185 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 138 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 64.1 24.00 0 43 0 0
#> 53 24.00 0 32 0 1
#> 131 24.00 0 66 0 0
#> 109 24.00 0 48 0 0
#> 12.1 24.00 0 63 0 0
#> 173.2 24.00 0 19 0 1
#> 182 24.00 0 35 0 0
#> 146 24.00 0 63 1 0
#> 102 24.00 0 49 0 0
#> 65.1 24.00 0 57 1 0
#> 80.1 24.00 0 41 0 0
#> 103 24.00 0 56 1 0
#> 172.1 24.00 0 41 0 0
#> 116 24.00 0 58 0 1
#> 34 24.00 0 36 0 0
#> 156 24.00 0 50 1 0
#> 80.2 24.00 0 41 0 0
#> 109.1 24.00 0 48 0 0
#> 151.1 24.00 0 42 0 0
#> 141 24.00 0 44 1 0
#> 191.1 24.00 0 60 0 1
#> 161 24.00 0 45 0 0
#> 22 24.00 0 52 1 0
#> 83 24.00 0 6 0 0
#> 7.1 24.00 0 37 1 0
#> 131.1 24.00 0 66 0 0
#> 46 24.00 0 71 0 0
#> 98.1 24.00 0 34 1 0
#> 185.1 24.00 0 44 1 0
#> 147.1 24.00 0 76 1 0
#> 132 24.00 0 55 0 0
#> 27.1 24.00 0 63 1 0
#> 65.2 24.00 0 57 1 0
#> 46.1 24.00 0 71 0 0
#> 62.2 24.00 0 71 0 0
#> 119 24.00 0 17 0 0
#> 151.2 24.00 0 42 0 0
#> 182.1 24.00 0 35 0 0
#> 144.1 24.00 0 28 0 1
#> 137 24.00 0 45 1 0
#> 53.1 24.00 0 32 0 1
#> 67.1 24.00 0 25 0 0
#> 163 24.00 0 66 0 0
#> 20 24.00 0 46 1 0
#> 142.1 24.00 0 53 0 0
#> 104.1 24.00 0 50 1 0
#> 11.2 24.00 0 42 0 1
#> 191.2 24.00 0 60 0 1
#> 17 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.19 NA NA NA
#> 2 age, Cure model 0.0262 NA NA NA
#> 3 grade_ii, Cure model -0.242 NA NA NA
#> 4 grade_iii, Cure model 0.645 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00934 NA NA NA
#> 2 grade_ii, Survival model 0.398 NA NA NA
#> 3 grade_iii, Survival model 0.107 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.18716 0.02624 -0.24153 0.64463
#>
#> Degrees of Freedom: 195 Total (i.e. Null); 192 Residual
#> Null Deviance: 269.7
#> Residual Deviance: 257.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.18716100 0.02623782 -0.24153106 0.64462794
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.009336814 0.397820419 0.107024367
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9345731 0.4236483 0.8862774 0.4636331 0.6022670 0.9802992 0.5278947
#> [8] 0.4341271 0.9604533 0.6326438 0.9186956 0.7299025 0.4341271 0.0780342
#> [15] 0.2321412 0.7494272 0.9553292 0.9025713 0.2485020 0.6176499 0.5365207
#> [22] 0.5784097 0.8231531 0.3190495 0.7619801 0.7989524 0.3574200 0.7744428
#> [29] 0.8695435 0.8526722 0.1769780 0.8526722 0.2795613 0.5944401 0.9852742
#> [36] 0.9501556 0.9186956 0.4732730 0.7989524 0.5864760 0.0780342 0.6619568
#> [43] 0.6619568 0.4341271 0.6401482 0.9604533 0.6899226 0.9133411 0.5014676
#> [50] 0.5535939 0.1964179 0.8751669 0.7035714 0.7364880 0.6547056 0.6022670
#> [57] 0.5702104 0.8468267 0.7744428 0.7494272 0.3914249 0.3574200 0.2145567
#> [64] 0.7619801 0.2795613 0.7035714 0.9902231 0.8526722 0.7035714 0.1566352
#> [71] 0.3325096 0.7035714 0.9604533 0.9902231 0.8862774 0.5191193 0.8291570
#> [78] 0.5014676 0.2795613 0.5450806 0.8409306 0.6176499 0.3325096 0.6619568
#> [85] 0.7364880 0.8862774 0.9604533 0.4828031 0.7744428 0.3574200 0.6829497
#> [92] 0.6401482 0.9292780 0.8807354 0.8111154 0.5535939 0.9025713 0.2642762
#> [99] 0.4130360 0.6899226 0.3914249 0.4921940 0.9345731 0.8111154 0.1316235
#> [106] 0.8291570 0.7928088 0.9345731 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 52 68 56 158 184 70 97 150 16 117 159 79 150.1
#> 10.42 20.62 12.21 20.14 17.77 7.38 19.14 20.33 8.71 17.46 10.55 16.23 20.33
#> 86 63 125 183 43 15 110 179 41 13 175 6 180
#> 23.81 22.77 15.65 9.24 12.10 22.68 17.56 18.63 18.02 14.34 21.91 15.64 14.82
#> 90 39 177 140 69 140.1 66 134 25 145 159.1 166 180.1
#> 20.94 15.59 12.53 12.68 23.23 12.68 22.13 17.81 6.32 10.07 10.55 19.98 14.82
#> 40 86.1 23 23.1 150.2 30 16.1 130 107 55 88 92 37
#> 18.00 23.81 16.92 16.92 20.33 17.43 8.71 16.47 11.18 19.34 18.37 22.92 12.52
#> 192 100 45 184.1 51 123 39.1 125.1 32 90.1 113 6.1 66.1
#> 16.44 16.07 17.42 17.77 18.23 13.00 15.59 15.65 20.90 20.94 22.86 15.64 22.13
#> 85 127 140.2 192.1 129 36 85.1 16.2 127.1 56.1 76 60 55.1
#> 16.44 3.53 12.68 16.44 23.41 21.19 16.44 8.71 3.53 12.21 19.22 13.15 19.34
#> 66.2 8 155 110.1 36.1 23.2 100.1 56.2 16.3 105 39.2 90.2 106
#> 22.13 18.43 13.08 17.56 21.19 16.92 16.07 12.21 8.71 19.75 15.59 20.94 16.67
#> 30.1 10 42 57 88.1 43.1 169 190 130.1 32.1 170 52.1 57.1
#> 17.43 10.53 12.43 14.46 18.37 12.10 22.41 20.81 16.47 20.90 19.54 10.42 14.46
#> 168 60.1 157 52.2 31 7 72 118 64 44 98 31.1 62
#> 23.72 13.15 15.10 10.42 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 11 191 147 152 82 62.1 152.1 148 65 151 104 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 144 12 48 186 11.1 80 173.1 48.1 121 172 121.1 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 27 138 196 64.1 53 131 109 12.1 173.2 182 146 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.1 80.1 103 172.1 116 34 156 80.2 109.1 151.1 141 191.1 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 83 7.1 131.1 46 98.1 185.1 147.1 132 27.1 65.2 46.1 62.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 151.2 182.1 144.1 137 53.1 67.1 163 20 142.1 104.1 11.2 191.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[62]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001320673 0.734936196 0.592046919
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.68941137 0.01713765 -0.51234538
#> grade_iii, Cure model
#> 0.80586914
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 78 23.88 1 43 0 0
#> 36 21.19 1 48 0 1
#> 24 23.89 1 38 0 0
#> 81 14.06 1 34 0 0
#> 139 21.49 1 63 1 0
#> 99 21.19 1 38 0 1
#> 113 22.86 1 34 0 0
#> 177 12.53 1 75 0 0
#> 159 10.55 1 50 0 1
#> 169 22.41 1 46 0 0
#> 15 22.68 1 48 0 0
#> 157 15.10 1 47 0 0
#> 92 22.92 1 47 0 1
#> 36.1 21.19 1 48 0 1
#> 183 9.24 1 67 1 0
#> 136 21.83 1 43 0 1
#> 199 19.81 1 NA 0 1
#> 164 23.60 1 76 0 1
#> 111 17.45 1 47 0 1
#> 184 17.77 1 38 0 0
#> 88 18.37 1 47 0 0
#> 23 16.92 1 61 0 0
#> 100 16.07 1 60 0 0
#> 93 10.33 1 52 0 1
#> 58 19.34 1 39 0 0
#> 168 23.72 1 70 0 0
#> 170 19.54 1 43 0 1
#> 66 22.13 1 53 0 0
#> 68 20.62 1 44 0 0
#> 37 12.52 1 57 1 0
#> 55 19.34 1 69 0 1
#> 89 11.44 1 NA 0 0
#> 187 9.92 1 39 1 0
#> 36.2 21.19 1 48 0 1
#> 90 20.94 1 50 0 1
#> 93.1 10.33 1 52 0 1
#> 4 17.64 1 NA 0 1
#> 63 22.77 1 31 1 0
#> 57 14.46 1 45 0 1
#> 30 17.43 1 78 0 0
#> 124 9.73 1 NA 1 0
#> 81.1 14.06 1 34 0 0
#> 167 15.55 1 56 1 0
#> 56 12.21 1 60 0 0
#> 10 10.53 1 34 0 0
#> 167.1 15.55 1 56 1 0
#> 168.1 23.72 1 70 0 0
#> 168.2 23.72 1 70 0 0
#> 42 12.43 1 49 0 1
#> 189 10.51 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 51 18.23 1 83 0 1
#> 177.1 12.53 1 75 0 0
#> 41 18.02 1 40 1 0
#> 189.1 10.51 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 100.1 16.07 1 60 0 0
#> 78.1 23.88 1 43 0 0
#> 123 13.00 1 44 1 0
#> 123.1 13.00 1 44 1 0
#> 129 23.41 1 53 1 0
#> 110 17.56 1 65 0 1
#> 49 12.19 1 48 1 0
#> 100.2 16.07 1 60 0 0
#> 45 17.42 1 54 0 1
#> 105 19.75 1 60 0 0
#> 105.1 19.75 1 60 0 0
#> 139.1 21.49 1 63 1 0
#> 91 5.33 1 61 0 1
#> 189.2 10.51 1 NA 1 0
#> 51.1 18.23 1 83 0 1
#> 150 20.33 1 48 0 0
#> 106 16.67 1 49 1 0
#> 180 14.82 1 37 0 0
#> 6 15.64 1 39 0 0
#> 8 18.43 1 32 0 0
#> 168.3 23.72 1 70 0 0
#> 111.1 17.45 1 47 0 1
#> 29 15.45 1 68 1 0
#> 14 12.89 1 21 0 0
#> 43 12.10 1 61 0 1
#> 91.1 5.33 1 61 0 1
#> 5 16.43 1 51 0 1
#> 70 7.38 1 30 1 0
#> 4.1 17.64 1 NA 0 1
#> 5.1 16.43 1 51 0 1
#> 90.1 20.94 1 50 0 1
#> 157.1 15.10 1 47 0 0
#> 18 15.21 1 49 1 0
#> 43.1 12.10 1 61 0 1
#> 106.1 16.67 1 49 1 0
#> 8.1 18.43 1 32 0 0
#> 175.1 21.91 1 43 0 0
#> 110.1 17.56 1 65 0 1
#> 153 21.33 1 55 1 0
#> 77 7.27 1 67 0 1
#> 6.1 15.64 1 39 0 0
#> 78.2 23.88 1 43 0 0
#> 167.2 15.55 1 56 1 0
#> 69 23.23 1 25 0 1
#> 96 14.54 1 33 0 1
#> 40 18.00 1 28 1 0
#> 4.2 17.64 1 NA 0 1
#> 68.1 20.62 1 44 0 0
#> 194 22.40 1 38 0 1
#> 8.2 18.43 1 32 0 0
#> 175.2 21.91 1 43 0 0
#> 66.1 22.13 1 53 0 0
#> 101 9.97 1 10 0 1
#> 70.1 7.38 1 30 1 0
#> 63.1 22.77 1 31 1 0
#> 13 14.34 1 54 0 1
#> 48 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 116 24.00 0 58 0 1
#> 9 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 172 24.00 0 41 0 0
#> 162 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#> 112 24.00 0 61 0 0
#> 118 24.00 0 44 1 0
#> 112.1 24.00 0 61 0 0
#> 33 24.00 0 53 0 0
#> 191 24.00 0 60 0 1
#> 34 24.00 0 36 0 0
#> 48.1 24.00 0 31 1 0
#> 48.2 24.00 0 31 1 0
#> 33.1 24.00 0 53 0 0
#> 135 24.00 0 58 1 0
#> 102 24.00 0 49 0 0
#> 178 24.00 0 52 1 0
#> 35 24.00 0 51 0 0
#> 33.2 24.00 0 53 0 0
#> 102.1 24.00 0 49 0 0
#> 9.1 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 34.1 24.00 0 36 0 0
#> 84 24.00 0 39 0 1
#> 161 24.00 0 45 0 0
#> 109 24.00 0 48 0 0
#> 122 24.00 0 66 0 0
#> 162.1 24.00 0 51 0 0
#> 174 24.00 0 49 1 0
#> 103 24.00 0 56 1 0
#> 3 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 103.1 24.00 0 56 1 0
#> 22 24.00 0 52 1 0
#> 165 24.00 0 47 0 0
#> 1 24.00 0 23 1 0
#> 95 24.00 0 68 0 1
#> 121 24.00 0 57 1 0
#> 156 24.00 0 50 1 0
#> 35.1 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 161.1 24.00 0 45 0 0
#> 165.1 24.00 0 47 0 0
#> 27 24.00 0 63 1 0
#> 1.1 24.00 0 23 1 0
#> 137 24.00 0 45 1 0
#> 33.3 24.00 0 53 0 0
#> 120 24.00 0 68 0 1
#> 178.1 24.00 0 52 1 0
#> 144 24.00 0 28 0 1
#> 120.1 24.00 0 68 0 1
#> 67 24.00 0 25 0 0
#> 9.2 24.00 0 31 1 0
#> 122.1 24.00 0 66 0 0
#> 103.2 24.00 0 56 1 0
#> 83 24.00 0 6 0 0
#> 33.4 24.00 0 53 0 0
#> 74 24.00 0 43 0 1
#> 28 24.00 0 67 1 0
#> 172.1 24.00 0 41 0 0
#> 38 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 103.3 24.00 0 56 1 0
#> 67.1 24.00 0 25 0 0
#> 98 24.00 0 34 1 0
#> 135.1 24.00 0 58 1 0
#> 103.4 24.00 0 56 1 0
#> 82 24.00 0 34 0 0
#> 116.1 24.00 0 58 0 1
#> 121.1 24.00 0 57 1 0
#> 9.3 24.00 0 31 1 0
#> 196.1 24.00 0 19 0 0
#> 135.2 24.00 0 58 1 0
#> 119 24.00 0 17 0 0
#> 33.5 24.00 0 53 0 0
#> 109.1 24.00 0 48 0 0
#> 35.2 24.00 0 51 0 0
#> 121.2 24.00 0 57 1 0
#> 75 24.00 0 21 1 0
#> 141 24.00 0 44 1 0
#> 102.2 24.00 0 49 0 0
#> 9.4 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 176.1 24.00 0 43 0 1
#> 137.1 24.00 0 45 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.689 NA NA NA
#> 2 age, Cure model 0.0171 NA NA NA
#> 3 grade_ii, Cure model -0.512 NA NA NA
#> 4 grade_iii, Cure model 0.806 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00132 NA NA NA
#> 2 grade_ii, Survival model 0.735 NA NA NA
#> 3 grade_iii, Survival model 0.592 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.68941 0.01714 -0.51235 0.80587
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 249.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.68941137 0.01713765 -0.51234538 0.80586914
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001320673 0.734936196 0.592046919
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.05686222 0.42819460 0.02196781 0.83380440 0.39613251 0.42819460
#> [7] 0.24834886 0.86749941 0.91999280 0.30049917 0.28776672 0.79214429
#> [13] 0.23386457 0.42819460 0.96401390 0.38441154 0.18396482 0.65027772
#> [19] 0.62578184 0.58295395 0.68185542 0.71973927 0.93277853 0.53897721
#> [25] 0.11562985 0.52989971 0.32544953 0.48400860 0.88083965 0.53897721
#> [31] 0.95783846 0.42819460 0.46561109 0.93277853 0.26279470 0.82006008
#> [37] 0.66607294 0.83380440 0.75669257 0.89405920 0.92638667 0.75669257
#> [43] 0.11562985 0.11562985 0.88747228 0.34936414 0.59184025 0.86749941
#> [49] 0.60896052 0.94535759 0.71973927 0.05686222 0.84742853 0.84742853
#> [55] 0.20214213 0.63412012 0.90064212 0.71973927 0.67400766 0.51161664
#> [61] 0.51161664 0.39613251 0.98817387 0.59184025 0.50236446 0.68969562
#> [67] 0.80610137 0.74187601 0.55667412 0.11562985 0.65027772 0.77803162
#> [73] 0.86079267 0.90716677 0.98817387 0.70486686 0.97013919 0.70486686
#> [79] 0.46561109 0.79214429 0.78512679 0.90716677 0.68969562 0.55667412
#> [85] 0.34936414 0.63412012 0.41764053 0.98217391 0.74187601 0.05686222
#> [91] 0.75669257 0.21850229 0.81310733 0.61743785 0.48400860 0.31319800
#> [97] 0.55667412 0.34936414 0.32544953 0.95161504 0.97013919 0.26279470
#> [103] 0.82695912 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 78 36 24 81 139 99 113 177 159 169 15 157 92
#> 23.88 21.19 23.89 14.06 21.49 21.19 22.86 12.53 10.55 22.41 22.68 15.10 22.92
#> 36.1 183 136 164 111 184 88 23 100 93 58 168 170
#> 21.19 9.24 21.83 23.60 17.45 17.77 18.37 16.92 16.07 10.33 19.34 23.72 19.54
#> 66 68 37 55 187 36.2 90 93.1 63 57 30 81.1 167
#> 22.13 20.62 12.52 19.34 9.92 21.19 20.94 10.33 22.77 14.46 17.43 14.06 15.55
#> 56 10 167.1 168.1 168.2 42 175 51 177.1 41 145 100.1 78.1
#> 12.21 10.53 15.55 23.72 23.72 12.43 21.91 18.23 12.53 18.02 10.07 16.07 23.88
#> 123 123.1 129 110 49 100.2 45 105 105.1 139.1 91 51.1 150
#> 13.00 13.00 23.41 17.56 12.19 16.07 17.42 19.75 19.75 21.49 5.33 18.23 20.33
#> 106 180 6 8 168.3 111.1 29 14 43 91.1 5 70 5.1
#> 16.67 14.82 15.64 18.43 23.72 17.45 15.45 12.89 12.10 5.33 16.43 7.38 16.43
#> 90.1 157.1 18 43.1 106.1 8.1 175.1 110.1 153 77 6.1 78.2 167.2
#> 20.94 15.10 15.21 12.10 16.67 18.43 21.91 17.56 21.33 7.27 15.64 23.88 15.55
#> 69 96 40 68.1 194 8.2 175.2 66.1 101 70.1 63.1 13 48
#> 23.23 14.54 18.00 20.62 22.40 18.43 21.91 22.13 9.97 7.38 22.77 14.34 24.00
#> 193 116 9 132 172 162 176 112 118 112.1 33 191 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.1 48.2 33.1 135 102 178 35 33.2 102.1 9.1 142 34.1 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 109 122 162.1 174 103 3 196 103.1 22 165 1 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 156 35.1 44 161.1 165.1 27 1.1 137 33.3 120 178.1 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 67 9.2 122.1 103.2 83 33.4 74 28 172.1 38 47 103.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.1 98 135.1 103.4 82 116.1 121.1 9.3 196.1 135.2 119 33.5 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.2 121.2 75 141 102.2 9.4 163 176.1 137.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[63]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006006562 0.333200353 0.228502595
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.42187692 0.02190194 0.51307471
#> grade_iii, Cure model
#> 1.06329984
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 4 17.64 1 NA 0 1
#> 30 17.43 1 78 0 0
#> 26 15.77 1 49 0 1
#> 81 14.06 1 34 0 0
#> 192 16.44 1 31 1 0
#> 197 21.60 1 69 1 0
#> 106 16.67 1 49 1 0
#> 85 16.44 1 36 0 0
#> 55 19.34 1 69 0 1
#> 63 22.77 1 31 1 0
#> 91 5.33 1 61 0 1
#> 111 17.45 1 47 0 1
#> 42 12.43 1 49 0 1
#> 90 20.94 1 50 0 1
#> 175 21.91 1 43 0 0
#> 101 9.97 1 10 0 1
#> 99 21.19 1 38 0 1
#> 187 9.92 1 39 1 0
#> 117 17.46 1 26 0 1
#> 195 11.76 1 NA 1 0
#> 190 20.81 1 42 1 0
#> 111.1 17.45 1 47 0 1
#> 32 20.90 1 37 1 0
#> 78 23.88 1 43 0 0
#> 192.1 16.44 1 31 1 0
#> 51 18.23 1 83 0 1
#> 4.1 17.64 1 NA 0 1
#> 91.1 5.33 1 61 0 1
#> 86 23.81 1 58 0 1
#> 128 20.35 1 35 0 1
#> 6 15.64 1 39 0 0
#> 5 16.43 1 51 0 1
#> 85.1 16.44 1 36 0 0
#> 77 7.27 1 67 0 1
#> 136 21.83 1 43 0 1
#> 127 3.53 1 62 0 1
#> 108 18.29 1 39 0 1
#> 194 22.40 1 38 0 1
#> 25 6.32 1 34 1 0
#> 166 19.98 1 48 0 0
#> 13 14.34 1 54 0 1
#> 97 19.14 1 65 0 1
#> 77.1 7.27 1 67 0 1
#> 56 12.21 1 60 0 0
#> 90.1 20.94 1 50 0 1
#> 133 14.65 1 57 0 0
#> 145 10.07 1 65 1 0
#> 111.2 17.45 1 47 0 1
#> 78.1 23.88 1 43 0 0
#> 15 22.68 1 48 0 0
#> 164 23.60 1 76 0 1
#> 129 23.41 1 53 1 0
#> 129.1 23.41 1 53 1 0
#> 192.2 16.44 1 31 1 0
#> 51.1 18.23 1 83 0 1
#> 145.1 10.07 1 65 1 0
#> 183 9.24 1 67 1 0
#> 76 19.22 1 54 0 1
#> 52 10.42 1 52 0 1
#> 105 19.75 1 60 0 0
#> 32.1 20.90 1 37 1 0
#> 127.1 3.53 1 62 0 1
#> 136.1 21.83 1 43 0 1
#> 37 12.52 1 57 1 0
#> 91.2 5.33 1 61 0 1
#> 105.1 19.75 1 60 0 0
#> 50 10.02 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 145.2 10.07 1 65 1 0
#> 16 8.71 1 71 0 1
#> 166.1 19.98 1 48 0 0
#> 123 13.00 1 44 1 0
#> 133.1 14.65 1 57 0 0
#> 40 18.00 1 28 1 0
#> 55.1 19.34 1 69 0 1
#> 154 12.63 1 20 1 0
#> 6.1 15.64 1 39 0 0
#> 51.2 18.23 1 83 0 1
#> 57 14.46 1 45 0 1
#> 125 15.65 1 67 1 0
#> 190.1 20.81 1 42 1 0
#> 4.2 17.64 1 NA 0 1
#> 194.1 22.40 1 38 0 1
#> 96 14.54 1 33 0 1
#> 130 16.47 1 53 0 1
#> 195.1 11.76 1 NA 1 0
#> 51.3 18.23 1 83 0 1
#> 96.1 14.54 1 33 0 1
#> 184 17.77 1 38 0 0
#> 26.1 15.77 1 49 0 1
#> 10 10.53 1 34 0 0
#> 189 10.51 1 NA 1 0
#> 106.1 16.67 1 49 1 0
#> 90.2 20.94 1 50 0 1
#> 145.3 10.07 1 65 1 0
#> 105.2 19.75 1 60 0 0
#> 26.2 15.77 1 49 0 1
#> 14 12.89 1 21 0 0
#> 153 21.33 1 55 1 0
#> 154.1 12.63 1 20 1 0
#> 175.1 21.91 1 43 0 0
#> 145.4 10.07 1 65 1 0
#> 91.3 5.33 1 61 0 1
#> 171 16.57 1 41 0 1
#> 128.1 20.35 1 35 0 1
#> 127.2 3.53 1 62 0 1
#> 177 12.53 1 75 0 0
#> 56.1 12.21 1 60 0 0
#> 107.1 11.18 1 54 1 0
#> 50.1 10.02 1 NA 1 0
#> 55.2 19.34 1 69 0 1
#> 23 16.92 1 61 0 0
#> 44 24.00 0 56 0 0
#> 74 24.00 0 43 0 1
#> 174 24.00 0 49 1 0
#> 9 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 48 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 161 24.00 0 45 0 0
#> 162 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 115 24.00 0 NA 1 0
#> 193 24.00 0 45 0 1
#> 172 24.00 0 41 0 0
#> 11 24.00 0 42 0 1
#> 122 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 118 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 144.1 24.00 0 28 0 1
#> 103 24.00 0 56 1 0
#> 94 24.00 0 51 0 1
#> 74.1 24.00 0 43 0 1
#> 156 24.00 0 50 1 0
#> 22 24.00 0 52 1 0
#> 162.1 24.00 0 51 0 0
#> 44.1 24.00 0 56 0 0
#> 22.1 24.00 0 52 1 0
#> 47 24.00 0 38 0 1
#> 138 24.00 0 44 1 0
#> 118.1 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 46 24.00 0 71 0 0
#> 54 24.00 0 53 1 0
#> 34 24.00 0 36 0 0
#> 151.1 24.00 0 42 0 0
#> 54.1 24.00 0 53 1 0
#> 80 24.00 0 41 0 0
#> 95 24.00 0 68 0 1
#> 35 24.00 0 51 0 0
#> 143 24.00 0 51 0 0
#> 71 24.00 0 51 0 0
#> 174.1 24.00 0 49 1 0
#> 67 24.00 0 25 0 0
#> 120 24.00 0 68 0 1
#> 172.1 24.00 0 41 0 0
#> 27 24.00 0 63 1 0
#> 104.1 24.00 0 50 1 0
#> 75 24.00 0 21 1 0
#> 186 24.00 0 45 1 0
#> 200 24.00 0 64 0 0
#> 160 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 138.1 24.00 0 44 1 0
#> 161.1 24.00 0 45 0 0
#> 33 24.00 0 53 0 0
#> 19 24.00 0 57 0 1
#> 176 24.00 0 43 0 1
#> 53 24.00 0 32 0 1
#> 12 24.00 0 63 0 0
#> 12.1 24.00 0 63 0 0
#> 131.1 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 131.2 24.00 0 66 0 0
#> 161.2 24.00 0 45 0 0
#> 162.2 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 152 24.00 0 36 0 1
#> 9.1 24.00 0 31 1 0
#> 95.1 24.00 0 68 0 1
#> 87 24.00 0 27 0 0
#> 173.1 24.00 0 19 0 1
#> 71.1 24.00 0 51 0 0
#> 143.1 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 53.1 24.00 0 32 0 1
#> 119 24.00 0 17 0 0
#> 120.1 24.00 0 68 0 1
#> 135 24.00 0 58 1 0
#> 21.1 24.00 0 47 0 0
#> 186.1 24.00 0 45 1 0
#> 115.1 24.00 0 NA 1 0
#> 102 24.00 0 49 0 0
#> 165 24.00 0 47 0 0
#> 84 24.00 0 39 0 1
#> 152.1 24.00 0 36 0 1
#> 74.2 24.00 0 43 0 1
#> 47.1 24.00 0 38 0 1
#> 147 24.00 0 76 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.42 NA NA NA
#> 2 age, Cure model 0.0219 NA NA NA
#> 3 grade_ii, Cure model 0.513 NA NA NA
#> 4 grade_iii, Cure model 1.06 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00601 NA NA NA
#> 2 grade_ii, Survival model 0.333 NA NA NA
#> 3 grade_iii, Survival model 0.229 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.4219 0.0219 0.5131 1.0633
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 248.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.42187692 0.02190194 0.51307471 1.06329984
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006006562 0.333200353 0.228502595
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.62434142 0.71317792 0.79623475 0.67020698 0.30911292 0.63996201
#> [7] 0.67020698 0.49020479 0.19170235 0.96002364 0.60096695 0.84287968
#> [13] 0.34682659 0.25420041 0.91806515 0.33458982 0.92417416 0.59285923
#> [19] 0.40135467 0.60096695 0.37990642 0.04945586 0.67020698 0.54415090
#> [25] 0.96002364 0.10706733 0.42192837 0.74126592 0.70593585 0.67020698
#> [31] 0.94228764 0.28249087 0.98297901 0.53529871 0.22495528 0.95411677
#> [37] 0.44196431 0.78945355 0.52635952 0.94228764 0.84941543 0.34682659
#> [43] 0.75516626 0.88785756 0.60096695 0.04945586 0.20854979 0.13459855
#> [49] 0.15754107 0.15754107 0.67020698 0.54415090 0.88785756 0.93025249
#> [55] 0.51728833 0.88149922 0.46170144 0.37990642 0.98297901 0.28249087
#> [61] 0.83630895 0.96002364 0.46170144 0.86235059 0.88785756 0.93628795
#> [67] 0.44196431 0.80300289 0.75516626 0.57650980 0.49020479 0.81643903
#> [73] 0.74126592 0.54415090 0.78262908 0.73424797 0.40135467 0.22495528
#> [79] 0.76896291 0.66269717 0.54415090 0.76896291 0.58469917 0.71317792
#> [85] 0.87510779 0.63996201 0.34682659 0.88785756 0.46170144 0.71317792
#> [91] 0.80972471 0.32208844 0.81643903 0.25420041 0.88785756 0.96002364
#> [97] 0.65512490 0.42192837 0.98297901 0.82968801 0.84941543 0.86235059
#> [103] 0.49020479 0.63217306 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 30 26 81 192 197 106 85 55 63 91 111 42 90
#> 17.43 15.77 14.06 16.44 21.60 16.67 16.44 19.34 22.77 5.33 17.45 12.43 20.94
#> 175 101 99 187 117 190 111.1 32 78 192.1 51 91.1 86
#> 21.91 9.97 21.19 9.92 17.46 20.81 17.45 20.90 23.88 16.44 18.23 5.33 23.81
#> 128 6 5 85.1 77 136 127 108 194 25 166 13 97
#> 20.35 15.64 16.43 16.44 7.27 21.83 3.53 18.29 22.40 6.32 19.98 14.34 19.14
#> 77.1 56 90.1 133 145 111.2 78.1 15 164 129 129.1 192.2 51.1
#> 7.27 12.21 20.94 14.65 10.07 17.45 23.88 22.68 23.60 23.41 23.41 16.44 18.23
#> 145.1 183 76 52 105 32.1 127.1 136.1 37 91.2 105.1 107 145.2
#> 10.07 9.24 19.22 10.42 19.75 20.90 3.53 21.83 12.52 5.33 19.75 11.18 10.07
#> 16 166.1 123 133.1 40 55.1 154 6.1 51.2 57 125 190.1 194.1
#> 8.71 19.98 13.00 14.65 18.00 19.34 12.63 15.64 18.23 14.46 15.65 20.81 22.40
#> 96 130 51.3 96.1 184 26.1 10 106.1 90.2 145.3 105.2 26.2 14
#> 14.54 16.47 18.23 14.54 17.77 15.77 10.53 16.67 20.94 10.07 19.75 15.77 12.89
#> 153 154.1 175.1 145.4 91.3 171 128.1 127.2 177 56.1 107.1 55.2 23
#> 21.33 12.63 21.91 10.07 5.33 16.57 20.35 3.53 12.53 12.21 11.18 19.34 16.92
#> 44 74 174 9 144 48 1 161 162 151 193 172 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 104 118 173 144.1 103 94 74.1 156 22 162.1 44.1 22.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 138 118.1 131 46 54 34 151.1 54.1 80 95 35 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 174.1 67 120 172.1 27 104.1 75 186 200 160 185 138.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.1 33 19 176 53 12 12.1 131.1 21 131.2 161.2 162.2 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 9.1 95.1 87 173.1 71.1 143.1 17 53.1 119 120.1 135 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.1 102 165 84 152.1 74.2 47.1 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[64]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004236375 0.824941598 0.305533284
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.59148138 -0.01133142 -0.25109360
#> grade_iii, Cure model
#> 0.64038720
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 14 12.89 1 21 0 0
#> 134 17.81 1 47 1 0
#> 145 10.07 1 65 1 0
#> 194 22.40 1 38 0 1
#> 49 12.19 1 48 1 0
#> 24 23.89 1 38 0 0
#> 79 16.23 1 54 1 0
#> 101 9.97 1 10 0 1
#> 105 19.75 1 60 0 0
#> 107 11.18 1 54 1 0
#> 61 10.12 1 36 0 1
#> 192 16.44 1 31 1 0
#> 92 22.92 1 47 0 1
#> 61.1 10.12 1 36 0 1
#> 8 18.43 1 32 0 0
#> 45 17.42 1 54 0 1
#> 124 9.73 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 85 16.44 1 36 0 0
#> 169 22.41 1 46 0 0
#> 124.1 9.73 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 89 11.44 1 NA 0 0
#> 52 10.42 1 52 0 1
#> 127 3.53 1 62 0 1
#> 13 14.34 1 54 0 1
#> 14.1 12.89 1 21 0 0
#> 184 17.77 1 38 0 0
#> 194.1 22.40 1 38 0 1
#> 32 20.90 1 37 1 0
#> 154 12.63 1 20 1 0
#> 56 12.21 1 60 0 0
#> 150 20.33 1 48 0 0
#> 97 19.14 1 65 0 1
#> 52.1 10.42 1 52 0 1
#> 10 10.53 1 34 0 0
#> 66 22.13 1 53 0 0
#> 133 14.65 1 57 0 0
#> 60.1 13.15 1 38 1 0
#> 10.1 10.53 1 34 0 0
#> 66.1 22.13 1 53 0 0
#> 40 18.00 1 28 1 0
#> 113 22.86 1 34 0 0
#> 136 21.83 1 43 0 1
#> 153 21.33 1 55 1 0
#> 159 10.55 1 50 0 1
#> 57 14.46 1 45 0 1
#> 167 15.55 1 56 1 0
#> 68 20.62 1 44 0 0
#> 140 12.68 1 59 1 0
#> 134.1 17.81 1 47 1 0
#> 14.2 12.89 1 21 0 0
#> 66.2 22.13 1 53 0 0
#> 149 8.37 1 33 1 0
#> 111 17.45 1 47 0 1
#> 42 12.43 1 49 0 1
#> 49.1 12.19 1 48 1 0
#> 97.1 19.14 1 65 0 1
#> 76 19.22 1 54 0 1
#> 91 5.33 1 61 0 1
#> 23 16.92 1 61 0 0
#> 15 22.68 1 48 0 0
#> 97.2 19.14 1 65 0 1
#> 171 16.57 1 41 0 1
#> 96 14.54 1 33 0 1
#> 88 18.37 1 47 0 0
#> 51 18.23 1 83 0 1
#> 5 16.43 1 51 0 1
#> 36 21.19 1 48 0 1
#> 14.3 12.89 1 21 0 0
#> 50 10.02 1 NA 1 0
#> 134.2 17.81 1 47 1 0
#> 89.1 11.44 1 NA 0 0
#> 125 15.65 1 67 1 0
#> 43 12.10 1 61 0 1
#> 123 13.00 1 44 1 0
#> 42.1 12.43 1 49 0 1
#> 91.1 5.33 1 61 0 1
#> 92.1 22.92 1 47 0 1
#> 192.1 16.44 1 31 1 0
#> 154.1 12.63 1 20 1 0
#> 100 16.07 1 60 0 0
#> 15.1 22.68 1 48 0 0
#> 130.1 16.47 1 53 0 1
#> 189 10.51 1 NA 1 0
#> 6 15.64 1 39 0 0
#> 199 19.81 1 NA 0 1
#> 85.1 16.44 1 36 0 0
#> 111.1 17.45 1 47 0 1
#> 86 23.81 1 58 0 1
#> 29 15.45 1 68 1 0
#> 93 10.33 1 52 0 1
#> 68.1 20.62 1 44 0 0
#> 145.1 10.07 1 65 1 0
#> 184.1 17.77 1 38 0 0
#> 39 15.59 1 37 0 1
#> 128 20.35 1 35 0 1
#> 42.2 12.43 1 49 0 1
#> 153.1 21.33 1 55 1 0
#> 128.1 20.35 1 35 0 1
#> 8.1 18.43 1 32 0 0
#> 41 18.02 1 40 1 0
#> 123.1 13.00 1 44 1 0
#> 100.1 16.07 1 60 0 0
#> 88.1 18.37 1 47 0 0
#> 108 18.29 1 39 0 1
#> 150.1 20.33 1 48 0 0
#> 125.1 15.65 1 67 1 0
#> 89.2 11.44 1 NA 0 0
#> 99 21.19 1 38 0 1
#> 187 9.92 1 39 1 0
#> 181 16.46 1 45 0 1
#> 98 24.00 0 34 1 0
#> 147 24.00 0 76 1 0
#> 7 24.00 0 37 1 0
#> 132 24.00 0 55 0 0
#> 191 24.00 0 60 0 1
#> 72 24.00 0 40 0 1
#> 65 24.00 0 57 1 0
#> 7.1 24.00 0 37 1 0
#> 35 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 156 24.00 0 50 1 0
#> 163 24.00 0 66 0 0
#> 47 24.00 0 38 0 1
#> 11 24.00 0 42 0 1
#> 146 24.00 0 63 1 0
#> 98.1 24.00 0 34 1 0
#> 186 24.00 0 45 1 0
#> 94 24.00 0 51 0 1
#> 62 24.00 0 71 0 0
#> 46 24.00 0 71 0 0
#> 122 24.00 0 66 0 0
#> 132.1 24.00 0 55 0 0
#> 156.1 24.00 0 50 1 0
#> 31 24.00 0 36 0 1
#> 20 24.00 0 46 1 0
#> 54 24.00 0 53 1 0
#> 163.1 24.00 0 66 0 0
#> 11.1 24.00 0 42 0 1
#> 1 24.00 0 23 1 0
#> 22 24.00 0 52 1 0
#> 103 24.00 0 56 1 0
#> 200 24.00 0 64 0 0
#> 116 24.00 0 58 0 1
#> 141 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 103.1 24.00 0 56 1 0
#> 152 24.00 0 36 0 1
#> 22.1 24.00 0 52 1 0
#> 185 24.00 0 44 1 0
#> 35.1 24.00 0 51 0 0
#> 3 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 126 24.00 0 48 0 0
#> 144 24.00 0 28 0 1
#> 65.1 24.00 0 57 1 0
#> 198 24.00 0 66 0 1
#> 132.2 24.00 0 55 0 0
#> 193 24.00 0 45 0 1
#> 102 24.00 0 49 0 0
#> 28 24.00 0 67 1 0
#> 21 24.00 0 47 0 0
#> 121 24.00 0 57 1 0
#> 19 24.00 0 57 0 1
#> 173 24.00 0 19 0 1
#> 131 24.00 0 66 0 0
#> 11.2 24.00 0 42 0 1
#> 156.2 24.00 0 50 1 0
#> 20.1 24.00 0 46 1 0
#> 74.1 24.00 0 43 0 1
#> 67 24.00 0 25 0 0
#> 102.1 24.00 0 49 0 0
#> 172 24.00 0 41 0 0
#> 64 24.00 0 43 0 0
#> 31.1 24.00 0 36 0 1
#> 34 24.00 0 36 0 0
#> 132.3 24.00 0 55 0 0
#> 178 24.00 0 52 1 0
#> 138 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 94.1 24.00 0 51 0 1
#> 54.1 24.00 0 53 1 0
#> 75 24.00 0 21 1 0
#> 165 24.00 0 47 0 0
#> 102.2 24.00 0 49 0 0
#> 54.2 24.00 0 53 1 0
#> 102.3 24.00 0 49 0 0
#> 118 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 115 24.00 0 NA 1 0
#> 84 24.00 0 39 0 1
#> 1.1 24.00 0 23 1 0
#> 151 24.00 0 42 0 0
#> 27 24.00 0 63 1 0
#> 196 24.00 0 19 0 0
#> 138.1 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 122.1 24.00 0 66 0 0
#> 33 24.00 0 53 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.591 NA NA NA
#> 2 age, Cure model -0.0113 NA NA NA
#> 3 grade_ii, Cure model -0.251 NA NA NA
#> 4 grade_iii, Cure model 0.640 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00424 NA NA NA
#> 2 grade_ii, Survival model 0.825 NA NA NA
#> 3 grade_iii, Survival model 0.306 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.59148 -0.01133 -0.25109 0.64039
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 256.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.59148138 -0.01133142 -0.25109360 0.64038720
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004236375 0.824941598 0.305533284
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.750359959 0.428676971 0.937592345 0.103046696 0.841345316 0.006165885
#> [7] 0.599096546 0.953331846 0.291109089 0.865560375 0.921656897 0.553320191
#> [13] 0.033664604 0.921656897 0.343636433 0.495511796 0.716261434 0.553320191
#> [19] 0.090116561 0.524566378 0.897638433 0.992247839 0.707393644 0.750359959
#> [25] 0.457081928 0.103046696 0.217946888 0.792291399 0.833109506 0.270144190
#> [31] 0.312612532 0.897638433 0.881620088 0.126457177 0.680715427 0.716261434
#> [37] 0.881620088 0.126457177 0.418384968 0.054588635 0.161821127 0.174459830
#> [43] 0.873593857 0.698516976 0.662858770 0.228511393 0.783851993 0.428676971
#> [49] 0.750359959 0.126457177 0.969037575 0.476340323 0.808699146 0.841345316
#> [55] 0.312612532 0.301876066 0.976798816 0.505177030 0.066665653 0.312612532
#> [61] 0.514884564 0.689626555 0.364807864 0.397008424 0.589776934 0.196360326
#> [67] 0.750359959 0.428676971 0.626690051 0.857465652 0.733487748 0.808699146
#> [73] 0.976798816 0.033664604 0.553320191 0.792291399 0.608299463 0.066665653
#> [79] 0.524566378 0.644701256 0.553320191 0.476340323 0.019959314 0.671829256
#> [85] 0.913631392 0.228511393 0.937592345 0.457081928 0.653790124 0.249475093
#> [91] 0.808699146 0.174459830 0.249475093 0.343636433 0.407826367 0.733487748
#> [97] 0.608299463 0.364807864 0.386203760 0.270144190 0.626690051 0.196360326
#> [103] 0.961214678 0.543692376 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 14 134 145 194 49 24 79 101 105 107 61 192 92
#> 12.89 17.81 10.07 22.40 12.19 23.89 16.23 9.97 19.75 11.18 10.12 16.44 22.92
#> 61.1 8 45 60 85 169 130 52 127 13 14.1 184 194.1
#> 10.12 18.43 17.42 13.15 16.44 22.41 16.47 10.42 3.53 14.34 12.89 17.77 22.40
#> 32 154 56 150 97 52.1 10 66 133 60.1 10.1 66.1 40
#> 20.90 12.63 12.21 20.33 19.14 10.42 10.53 22.13 14.65 13.15 10.53 22.13 18.00
#> 113 136 153 159 57 167 68 140 134.1 14.2 66.2 149 111
#> 22.86 21.83 21.33 10.55 14.46 15.55 20.62 12.68 17.81 12.89 22.13 8.37 17.45
#> 42 49.1 97.1 76 91 23 15 97.2 171 96 88 51 5
#> 12.43 12.19 19.14 19.22 5.33 16.92 22.68 19.14 16.57 14.54 18.37 18.23 16.43
#> 36 14.3 134.2 125 43 123 42.1 91.1 92.1 192.1 154.1 100 15.1
#> 21.19 12.89 17.81 15.65 12.10 13.00 12.43 5.33 22.92 16.44 12.63 16.07 22.68
#> 130.1 6 85.1 111.1 86 29 93 68.1 145.1 184.1 39 128 42.2
#> 16.47 15.64 16.44 17.45 23.81 15.45 10.33 20.62 10.07 17.77 15.59 20.35 12.43
#> 153.1 128.1 8.1 41 123.1 100.1 88.1 108 150.1 125.1 99 187 181
#> 21.33 20.35 18.43 18.02 13.00 16.07 18.37 18.29 20.33 15.65 21.19 9.92 16.46
#> 98 147 7 132 191 72 65 7.1 35 109 156 163 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 146 98.1 186 94 62 46 122 132.1 156.1 31 20 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163.1 11.1 1 22 103 200 116 141 119 103.1 152 22.1 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.1 3 74 126 144 65.1 198 132.2 193 102 28 21 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 173 131 11.2 156.2 20.1 74.1 67 102.1 172 64 31.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.3 178 138 38 94.1 54.1 75 165 102.2 54.2 102.3 118 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 1.1 151 27 196 138.1 142 122.1 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[65]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001517047 0.475408509 0.351113517
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.85904811 0.01634257 -0.11144219
#> grade_iii, Cure model
#> 0.85786536
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 197 21.60 1 69 1 0
#> 66 22.13 1 53 0 0
#> 52 10.42 1 52 0 1
#> 96 14.54 1 33 0 1
#> 111 17.45 1 47 0 1
#> 36 21.19 1 48 0 1
#> 188 16.16 1 46 0 1
#> 195 11.76 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 117 17.46 1 26 0 1
#> 63 22.77 1 31 1 0
#> 45 17.42 1 54 0 1
#> 136 21.83 1 43 0 1
#> 190 20.81 1 42 1 0
#> 5 16.43 1 51 0 1
#> 85 16.44 1 36 0 0
#> 77 7.27 1 67 0 1
#> 183 9.24 1 67 1 0
#> 128 20.35 1 35 0 1
#> 51 18.23 1 83 0 1
#> 192 16.44 1 31 1 0
#> 105 19.75 1 60 0 0
#> 70 7.38 1 30 1 0
#> 97 19.14 1 65 0 1
#> 145 10.07 1 65 1 0
#> 166 19.98 1 48 0 0
#> 194 22.40 1 38 0 1
#> 40 18.00 1 28 1 0
#> 114 13.68 1 NA 0 0
#> 93 10.33 1 52 0 1
#> 155 13.08 1 26 0 0
#> 13 14.34 1 54 0 1
#> 145.1 10.07 1 65 1 0
#> 59 10.16 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 114.1 13.68 1 NA 0 0
#> 183.1 9.24 1 67 1 0
#> 111.1 17.45 1 47 0 1
#> 29 15.45 1 68 1 0
#> 92 22.92 1 47 0 1
#> 188.1 16.16 1 46 0 1
#> 6 15.64 1 39 0 0
#> 77.1 7.27 1 67 0 1
#> 41 18.02 1 40 1 0
#> 18 15.21 1 49 1 0
#> 157 15.10 1 47 0 0
#> 157.1 15.10 1 47 0 0
#> 93.1 10.33 1 52 0 1
#> 113 22.86 1 34 0 0
#> 106 16.67 1 49 1 0
#> 133 14.65 1 57 0 0
#> 45.1 17.42 1 54 0 1
#> 45.2 17.42 1 54 0 1
#> 192.1 16.44 1 31 1 0
#> 8 18.43 1 32 0 0
#> 139 21.49 1 63 1 0
#> 113.1 22.86 1 34 0 0
#> 51.1 18.23 1 83 0 1
#> 79 16.23 1 54 1 0
#> 42 12.43 1 49 0 1
#> 93.2 10.33 1 52 0 1
#> 130 16.47 1 53 0 1
#> 125 15.65 1 67 1 0
#> 184 17.77 1 38 0 0
#> 18.1 15.21 1 49 1 0
#> 101 9.97 1 10 0 1
#> 175 21.91 1 43 0 0
#> 170 19.54 1 43 0 1
#> 92.1 22.92 1 47 0 1
#> 52.1 10.42 1 52 0 1
#> 180 14.82 1 37 0 0
#> 99 21.19 1 38 0 1
#> 129 23.41 1 53 1 0
#> 91 5.33 1 61 0 1
#> 61 10.12 1 36 0 1
#> 79.1 16.23 1 54 1 0
#> 114.2 13.68 1 NA 0 0
#> 145.2 10.07 1 65 1 0
#> 105.1 19.75 1 60 0 0
#> 69 23.23 1 25 0 1
#> 169 22.41 1 46 0 0
#> 81 14.06 1 34 0 0
#> 158 20.14 1 74 1 0
#> 29.1 15.45 1 68 1 0
#> 66.1 22.13 1 53 0 0
#> 25 6.32 1 34 1 0
#> 68 20.62 1 44 0 0
#> 90 20.94 1 50 0 1
#> 110 17.56 1 65 0 1
#> 195.1 11.76 1 NA 1 0
#> 50 10.02 1 NA 1 0
#> 117.1 17.46 1 26 0 1
#> 32 20.90 1 37 1 0
#> 91.1 5.33 1 61 0 1
#> 50.1 10.02 1 NA 1 0
#> 61.1 10.12 1 36 0 1
#> 59.1 10.16 1 NA 1 0
#> 114.3 13.68 1 NA 0 0
#> 78 23.88 1 43 0 0
#> 181 16.46 1 45 0 1
#> 89 11.44 1 NA 0 0
#> 6.1 15.64 1 39 0 0
#> 188.2 16.16 1 46 0 1
#> 192.2 16.44 1 31 1 0
#> 42.1 12.43 1 49 0 1
#> 150 20.33 1 48 0 0
#> 123 13.00 1 44 1 0
#> 164 23.60 1 76 0 1
#> 155.1 13.08 1 26 0 0
#> 153 21.33 1 55 1 0
#> 76 19.22 1 54 0 1
#> 125.1 15.65 1 67 1 0
#> 162 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 54 24.00 0 53 1 0
#> 74 24.00 0 43 0 1
#> 11 24.00 0 42 0 1
#> 98 24.00 0 34 1 0
#> 75 24.00 0 21 1 0
#> 7 24.00 0 37 1 0
#> 122 24.00 0 66 0 0
#> 109 24.00 0 48 0 0
#> 147 24.00 0 76 1 0
#> 176 24.00 0 43 0 1
#> 161 24.00 0 45 0 0
#> 165 24.00 0 47 0 0
#> 103 24.00 0 56 1 0
#> 160 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 53 24.00 0 32 0 1
#> 161.1 24.00 0 45 0 0
#> 64 24.00 0 43 0 0
#> 11.1 24.00 0 42 0 1
#> 33 24.00 0 53 0 0
#> 165.1 24.00 0 47 0 0
#> 28 24.00 0 67 1 0
#> 46 24.00 0 71 0 0
#> 173 24.00 0 19 0 1
#> 132 24.00 0 55 0 0
#> 138 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 142 24.00 0 53 0 0
#> 34 24.00 0 36 0 0
#> 28.1 24.00 0 67 1 0
#> 95 24.00 0 68 0 1
#> 75.1 24.00 0 21 1 0
#> 44 24.00 0 56 0 0
#> 120 24.00 0 68 0 1
#> 173.1 24.00 0 19 0 1
#> 11.2 24.00 0 42 0 1
#> 3 24.00 0 31 1 0
#> 98.1 24.00 0 34 1 0
#> 31 24.00 0 36 0 1
#> 71 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 102 24.00 0 49 0 0
#> 138.1 24.00 0 44 1 0
#> 98.2 24.00 0 34 1 0
#> 84 24.00 0 39 0 1
#> 64.1 24.00 0 43 0 0
#> 73 24.00 0 NA 0 1
#> 46.1 24.00 0 71 0 0
#> 121 24.00 0 57 1 0
#> 67 24.00 0 25 0 0
#> 185.1 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 122.1 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 72 24.00 0 40 0 1
#> 87 24.00 0 27 0 0
#> 185.2 24.00 0 44 1 0
#> 73.1 24.00 0 NA 0 1
#> 94 24.00 0 51 0 1
#> 27 24.00 0 63 1 0
#> 152 24.00 0 36 0 1
#> 103.1 24.00 0 56 1 0
#> 112 24.00 0 61 0 0
#> 3.1 24.00 0 31 1 0
#> 74.1 24.00 0 43 0 1
#> 172 24.00 0 41 0 0
#> 161.2 24.00 0 45 0 0
#> 9.1 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 196 24.00 0 19 0 0
#> 135 24.00 0 58 1 0
#> 3.2 24.00 0 31 1 0
#> 135.1 24.00 0 58 1 0
#> 116 24.00 0 58 0 1
#> 53.1 24.00 0 32 0 1
#> 121.1 24.00 0 57 1 0
#> 148 24.00 0 61 1 0
#> 7.1 24.00 0 37 1 0
#> 35 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 186.1 24.00 0 45 1 0
#> 121.2 24.00 0 57 1 0
#> 104 24.00 0 50 1 0
#> 84.1 24.00 0 39 0 1
#> 94.1 24.00 0 51 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.859 NA NA NA
#> 2 age, Cure model 0.0163 NA NA NA
#> 3 grade_ii, Cure model -0.111 NA NA NA
#> 4 grade_iii, Cure model 0.858 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00152 NA NA NA
#> 2 grade_ii, Survival model 0.475 NA NA NA
#> 3 grade_iii, Survival model 0.351 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.85905 0.01634 -0.11144 0.85787
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 247.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.85904811 0.01634257 -0.11144219 0.85786536
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001517047 0.475408509 0.351113517
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.28161474 0.22914787 0.86833702 0.80925644 0.56004885 0.31815065
#> [7] 0.69467728 0.18746573 0.54198203 0.17329643 0.57781450 0.26859621
#> [13] 0.36257877 0.67044810 0.63801643 0.96640308 0.94588660 0.38393823
#> [19] 0.48550460 0.63801643 0.42552302 0.95957016 0.46579876 0.91819120
#> [25] 0.41525320 0.21557414 0.51401157 0.88277210 0.83160092 0.81673037
#> [31] 0.91819120 0.60361746 0.94588660 0.56004885 0.74907454 0.11557153
#> [37] 0.69467728 0.73362300 0.96640308 0.50453361 0.76428037 0.77926770
#> [43] 0.77926770 0.88277210 0.14457624 0.61233179 0.80174828 0.57781450
#> [49] 0.57781450 0.63801643 0.47565675 0.29417689 0.14457624 0.48550460
#> [55] 0.67865332 0.85377186 0.88277210 0.62095617 0.71815160 0.52337244
#> [61] 0.76428037 0.93894116 0.25524367 0.44572319 0.11557153 0.86833702
#> [67] 0.79423376 0.31815065 0.07769765 0.98665696 0.90405667 0.67865332
#> [73] 0.91819120 0.42552302 0.09749866 0.20155514 0.82416742 0.40496419
#> [79] 0.74907454 0.22914787 0.97991162 0.37326904 0.34049507 0.53272338
#> [85] 0.54198203 0.35165850 0.98665696 0.90405667 0.02091092 0.62951641
#> [91] 0.73362300 0.69467728 0.63801643 0.85377186 0.39446178 0.84639090
#> [97] 0.05336316 0.83160092 0.30633926 0.45582086 0.71815160 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 197 66 52 96 111 36 188 15 117 63 45 136 190
#> 21.60 22.13 10.42 14.54 17.45 21.19 16.16 22.68 17.46 22.77 17.42 21.83 20.81
#> 5 85 77 183 128 51 192 105 70 97 145 166 194
#> 16.43 16.44 7.27 9.24 20.35 18.23 16.44 19.75 7.38 19.14 10.07 19.98 22.40
#> 40 93 155 13 145.1 23 183.1 111.1 29 92 188.1 6 77.1
#> 18.00 10.33 13.08 14.34 10.07 16.92 9.24 17.45 15.45 22.92 16.16 15.64 7.27
#> 41 18 157 157.1 93.1 113 106 133 45.1 45.2 192.1 8 139
#> 18.02 15.21 15.10 15.10 10.33 22.86 16.67 14.65 17.42 17.42 16.44 18.43 21.49
#> 113.1 51.1 79 42 93.2 130 125 184 18.1 101 175 170 92.1
#> 22.86 18.23 16.23 12.43 10.33 16.47 15.65 17.77 15.21 9.97 21.91 19.54 22.92
#> 52.1 180 99 129 91 61 79.1 145.2 105.1 69 169 81 158
#> 10.42 14.82 21.19 23.41 5.33 10.12 16.23 10.07 19.75 23.23 22.41 14.06 20.14
#> 29.1 66.1 25 68 90 110 117.1 32 91.1 61.1 78 181 6.1
#> 15.45 22.13 6.32 20.62 20.94 17.56 17.46 20.90 5.33 10.12 23.88 16.46 15.64
#> 188.2 192.2 42.1 150 123 164 155.1 153 76 125.1 162 137 54
#> 16.16 16.44 12.43 20.33 13.00 23.60 13.08 21.33 19.22 15.65 24.00 24.00 24.00
#> 74 11 98 75 7 122 109 147 176 161 165 103 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 53 161.1 64 11.1 33 165.1 28 46 173 132 138 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 142 34 28.1 95 75.1 44 120 173.1 11.2 3 98.1 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 185 102 138.1 98.2 84 64.1 46.1 121 67 185.1 62 122.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 72 87 185.2 94 27 152 103.1 112 3.1 74.1 172 161.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 186 196 135 3.2 135.1 116 53.1 121.1 148 7.1 35 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.1 121.2 104 84.1 94.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[66]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01079658 0.36022904 0.45475961
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.06877809 0.02453311 0.12071650
#> grade_iii, Cure model
#> 0.29307203
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 42 12.43 1 49 0 1
#> 69 23.23 1 25 0 1
#> 134 17.81 1 47 1 0
#> 63 22.77 1 31 1 0
#> 125 15.65 1 67 1 0
#> 90 20.94 1 50 0 1
#> 40 18.00 1 28 1 0
#> 68 20.62 1 44 0 0
#> 111 17.45 1 47 0 1
#> 85 16.44 1 36 0 0
#> 16 8.71 1 71 0 1
#> 127 3.53 1 62 0 1
#> 113 22.86 1 34 0 0
#> 29 15.45 1 68 1 0
#> 136 21.83 1 43 0 1
#> 81 14.06 1 34 0 0
#> 40.1 18.00 1 28 1 0
#> 78 23.88 1 43 0 0
#> 105 19.75 1 60 0 0
#> 188 16.16 1 46 0 1
#> 6 15.64 1 39 0 0
#> 145 10.07 1 65 1 0
#> 100 16.07 1 60 0 0
#> 16.1 8.71 1 71 0 1
#> 150 20.33 1 48 0 0
#> 45 17.42 1 54 0 1
#> 81.1 14.06 1 34 0 0
#> 127.1 3.53 1 62 0 1
#> 197 21.60 1 69 1 0
#> 91 5.33 1 61 0 1
#> 125.1 15.65 1 67 1 0
#> 140 12.68 1 59 1 0
#> 157 15.10 1 47 0 0
#> 192 16.44 1 31 1 0
#> 85.1 16.44 1 36 0 0
#> 195 11.76 1 NA 1 0
#> 134.1 17.81 1 47 1 0
#> 183 9.24 1 67 1 0
#> 181 16.46 1 45 0 1
#> 85.2 16.44 1 36 0 0
#> 197.1 21.60 1 69 1 0
#> 43 12.10 1 61 0 1
#> 177 12.53 1 75 0 0
#> 85.3 16.44 1 36 0 0
#> 177.1 12.53 1 75 0 0
#> 159 10.55 1 50 0 1
#> 183.1 9.24 1 67 1 0
#> 77 7.27 1 67 0 1
#> 169 22.41 1 46 0 0
#> 106 16.67 1 49 1 0
#> 171 16.57 1 41 0 1
#> 168 23.72 1 70 0 0
#> 123 13.00 1 44 1 0
#> 50 10.02 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 18 15.21 1 49 1 0
#> 105.1 19.75 1 60 0 0
#> 139 21.49 1 63 1 0
#> 177.2 12.53 1 75 0 0
#> 125.2 15.65 1 67 1 0
#> 113.1 22.86 1 34 0 0
#> 66 22.13 1 53 0 0
#> 18.1 15.21 1 49 1 0
#> 184 17.77 1 38 0 0
#> 179 18.63 1 42 0 0
#> 166 19.98 1 48 0 0
#> 117 17.46 1 26 0 1
#> 36 21.19 1 48 0 1
#> 76.1 19.22 1 54 0 1
#> 181.1 16.46 1 45 0 1
#> 179.1 18.63 1 42 0 0
#> 10 10.53 1 34 0 0
#> 90.1 20.94 1 50 0 1
#> 23 16.92 1 61 0 0
#> 192.1 16.44 1 31 1 0
#> 190 20.81 1 42 1 0
#> 37 12.52 1 57 1 0
#> 197.2 21.60 1 69 1 0
#> 49 12.19 1 48 1 0
#> 187 9.92 1 39 1 0
#> 70 7.38 1 30 1 0
#> 167 15.55 1 56 1 0
#> 130 16.47 1 53 0 1
#> 195.1 11.76 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 123.1 13.00 1 44 1 0
#> 30 17.43 1 78 0 0
#> 89 11.44 1 NA 0 0
#> 190.1 20.81 1 42 1 0
#> 39 15.59 1 37 0 1
#> 150.1 20.33 1 48 0 0
#> 150.2 20.33 1 48 0 0
#> 13 14.34 1 54 0 1
#> 41 18.02 1 40 1 0
#> 6.1 15.64 1 39 0 0
#> 13.1 14.34 1 54 0 1
#> 192.2 16.44 1 31 1 0
#> 197.3 21.60 1 69 1 0
#> 170 19.54 1 43 0 1
#> 154 12.63 1 20 1 0
#> 177.3 12.53 1 75 0 0
#> 134.2 17.81 1 47 1 0
#> 136.1 21.83 1 43 0 1
#> 187.1 9.92 1 39 1 0
#> 113.2 22.86 1 34 0 0
#> 81.2 14.06 1 34 0 0
#> 187.2 9.92 1 39 1 0
#> 59 10.16 1 NA 1 0
#> 18.2 15.21 1 49 1 0
#> 192.3 16.44 1 31 1 0
#> 5 16.43 1 51 0 1
#> 129 23.41 1 53 1 0
#> 161 24.00 0 45 0 0
#> 196 24.00 0 19 0 0
#> 34 24.00 0 36 0 0
#> 28 24.00 0 67 1 0
#> 46 24.00 0 71 0 0
#> 141 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 28.1 24.00 0 67 1 0
#> 67 24.00 0 25 0 0
#> 191 24.00 0 60 0 1
#> 160 24.00 0 31 1 0
#> 9.1 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 146 24.00 0 63 1 0
#> 193 24.00 0 45 0 1
#> 191.1 24.00 0 60 0 1
#> 31 24.00 0 36 0 1
#> 82 24.00 0 34 0 0
#> 174 24.00 0 49 1 0
#> 47 24.00 0 38 0 1
#> 116 24.00 0 58 0 1
#> 122 24.00 0 66 0 0
#> 3 24.00 0 31 1 0
#> 94 24.00 0 51 0 1
#> 46.1 24.00 0 71 0 0
#> 28.2 24.00 0 67 1 0
#> 156 24.00 0 50 1 0
#> 94.1 24.00 0 51 0 1
#> 35 24.00 0 51 0 0
#> 71.1 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 144 24.00 0 28 0 1
#> 9.2 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 67.1 24.00 0 25 0 0
#> 72 24.00 0 40 0 1
#> 122.1 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 21 24.00 0 47 0 0
#> 142 24.00 0 53 0 0
#> 178 24.00 0 52 1 0
#> 1 24.00 0 23 1 0
#> 80 24.00 0 41 0 0
#> 137 24.00 0 45 1 0
#> 191.2 24.00 0 60 0 1
#> 103 24.00 0 56 1 0
#> 64 24.00 0 43 0 0
#> 126 24.00 0 48 0 0
#> 178.1 24.00 0 52 1 0
#> 47.1 24.00 0 38 0 1
#> 143 24.00 0 51 0 0
#> 94.2 24.00 0 51 0 1
#> 82.1 24.00 0 34 0 0
#> 98 24.00 0 34 1 0
#> 138.1 24.00 0 44 1 0
#> 71.2 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 19 24.00 0 57 0 1
#> 178.2 24.00 0 52 1 0
#> 121 24.00 0 57 1 0
#> 72.1 24.00 0 40 0 1
#> 186 24.00 0 45 1 0
#> 102 24.00 0 49 0 0
#> 126.1 24.00 0 48 0 0
#> 161.1 24.00 0 45 0 0
#> 143.1 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 20 24.00 0 46 1 0
#> 82.2 24.00 0 34 0 0
#> 72.2 24.00 0 40 0 1
#> 75 24.00 0 21 1 0
#> 83 24.00 0 6 0 0
#> 31.1 24.00 0 36 0 1
#> 172 24.00 0 41 0 0
#> 178.3 24.00 0 52 1 0
#> 20.1 24.00 0 46 1 0
#> 148 24.00 0 61 1 0
#> 162 24.00 0 51 0 0
#> 72.3 24.00 0 40 0 1
#> 83.1 24.00 0 6 0 0
#> 7 24.00 0 37 1 0
#> 7.1 24.00 0 37 1 0
#> 109 24.00 0 48 0 0
#> 80.1 24.00 0 41 0 0
#> 65 24.00 0 57 1 0
#> 152 24.00 0 36 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.07 NA NA NA
#> 2 age, Cure model 0.0245 NA NA NA
#> 3 grade_ii, Cure model 0.121 NA NA NA
#> 4 grade_iii, Cure model 0.293 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0108 NA NA NA
#> 2 grade_ii, Survival model 0.360 NA NA NA
#> 3 grade_iii, Survival model 0.455 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.06878 0.02453 0.12072 0.29307
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 260.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.06877809 0.02453311 0.12071650 0.29307203
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01079658 0.36022904 0.45475961
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.92161502 0.20629370 0.62315112 0.29485286 0.78392641 0.45607265
#> [7] 0.60778399 0.49553456 0.65948086 0.71965486 0.97083441 0.99186094
#> [13] 0.23262399 0.82240673 0.35473210 0.86364208 0.60778399 0.07167619
#> [19] 0.54143672 0.77227119 0.80050569 0.94452594 0.77811869 0.97083441
#> [25] 0.50512441 0.67357192 0.86364208 0.99186094 0.38683107 0.98771215
#> [31] 0.78392641 0.88839266 0.84325710 0.71965486 0.71965486 0.62315112
#> [37] 0.96218614 0.70706626 0.71965486 0.38683107 0.93088879 0.89813646
#> [43] 0.71965486 0.89813646 0.93546293 0.96218614 0.98352742 0.31566899
#> [49] 0.68724058 0.69394777 0.13439230 0.87856283 0.56762015 0.82775210
#> [55] 0.54143672 0.43343006 0.89813646 0.78392641 0.23262399 0.33563888
#> [61] 0.82775210 0.64495225 0.58386864 0.53231991 0.65226051 0.44498826
#> [67] 0.56762015 0.70706626 0.58386864 0.93999928 0.45607265 0.68043824
#> [73] 0.71965486 0.47631650 0.91692212 0.38683107 0.92626824 0.94901192
#> [79] 0.97930227 0.81699142 0.70056206 0.84843632 0.87856283 0.66657559
#> [85] 0.47631650 0.81151717 0.50512441 0.50512441 0.85358880 0.59986181
#> [91] 0.80050569 0.85358880 0.71965486 0.38683107 0.55898297 0.89327491
#> [97] 0.89813646 0.62315112 0.35473210 0.94901192 0.23262399 0.86364208
#> [103] 0.94901192 0.82775210 0.71965486 0.76635247 0.17584032 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000
#>
#> $Time
#> 42 69 134 63 125 90 40 68 111 85 16 127 113
#> 12.43 23.23 17.81 22.77 15.65 20.94 18.00 20.62 17.45 16.44 8.71 3.53 22.86
#> 29 136 81 40.1 78 105 188 6 145 100 16.1 150 45
#> 15.45 21.83 14.06 18.00 23.88 19.75 16.16 15.64 10.07 16.07 8.71 20.33 17.42
#> 81.1 127.1 197 91 125.1 140 157 192 85.1 134.1 183 181 85.2
#> 14.06 3.53 21.60 5.33 15.65 12.68 15.10 16.44 16.44 17.81 9.24 16.46 16.44
#> 197.1 43 177 85.3 177.1 159 183.1 77 169 106 171 168 123
#> 21.60 12.10 12.53 16.44 12.53 10.55 9.24 7.27 22.41 16.67 16.57 23.72 13.00
#> 76 18 105.1 139 177.2 125.2 113.1 66 18.1 184 179 166 117
#> 19.22 15.21 19.75 21.49 12.53 15.65 22.86 22.13 15.21 17.77 18.63 19.98 17.46
#> 36 76.1 181.1 179.1 10 90.1 23 192.1 190 37 197.2 49 187
#> 21.19 19.22 16.46 18.63 10.53 20.94 16.92 16.44 20.81 12.52 21.60 12.19 9.92
#> 70 167 130 133 123.1 30 190.1 39 150.1 150.2 13 41 6.1
#> 7.38 15.55 16.47 14.65 13.00 17.43 20.81 15.59 20.33 20.33 14.34 18.02 15.64
#> 13.1 192.2 197.3 170 154 177.3 134.2 136.1 187.1 113.2 81.2 187.2 18.2
#> 14.34 16.44 21.60 19.54 12.63 12.53 17.81 21.83 9.92 22.86 14.06 9.92 15.21
#> 192.3 5 129 161 196 34 28 46 141 71 9 104 28.1
#> 16.44 16.43 23.41 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 191 160 9.1 22 146 193 191.1 31 82 174 47 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 3 94 46.1 28.2 156 94.1 35 71.1 44 144 9.2 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.1 72 122.1 84 21 142 178 1 80 137 191.2 103 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 178.1 47.1 143 94.2 82.1 98 138.1 71.2 19 178.2 121 72.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 102 126.1 161.1 143.1 2 20 82.2 72.2 75 83 31.1 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178.3 20.1 148 162 72.3 83.1 7 7.1 109 80.1 65 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[67]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00910622 1.17469684 0.14366265
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.50276845 0.01639735 -0.27893393
#> grade_iii, Cure model
#> 0.12400950
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 194 22.40 1 38 0 1
#> 45 17.42 1 54 0 1
#> 123 13.00 1 44 1 0
#> 13 14.34 1 54 0 1
#> 113 22.86 1 34 0 0
#> 50 10.02 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 85 16.44 1 36 0 0
#> 113.1 22.86 1 34 0 0
#> 107 11.18 1 54 1 0
#> 85.1 16.44 1 36 0 0
#> 85.2 16.44 1 36 0 0
#> 124 9.73 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 81 14.06 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 134 17.81 1 47 1 0
#> 194.1 22.40 1 38 0 1
#> 179 18.63 1 42 0 0
#> 57 14.46 1 45 0 1
#> 153 21.33 1 55 1 0
#> 117 17.46 1 26 0 1
#> 25 6.32 1 34 1 0
#> 29 15.45 1 68 1 0
#> 79 16.23 1 54 1 0
#> 49 12.19 1 48 1 0
#> 140 12.68 1 59 1 0
#> 13.1 14.34 1 54 0 1
#> 55 19.34 1 69 0 1
#> 107.1 11.18 1 54 1 0
#> 158 20.14 1 74 1 0
#> 105 19.75 1 60 0 0
#> 41 18.02 1 40 1 0
#> 128 20.35 1 35 0 1
#> 25.1 6.32 1 34 1 0
#> 180 14.82 1 37 0 0
#> 43 12.10 1 61 0 1
#> 130 16.47 1 53 0 1
#> 145 10.07 1 65 1 0
#> 199 19.81 1 NA 0 1
#> 49.1 12.19 1 48 1 0
#> 130.1 16.47 1 53 0 1
#> 106 16.67 1 49 1 0
#> 86 23.81 1 58 0 1
#> 100.1 16.07 1 60 0 0
#> 105.1 19.75 1 60 0 0
#> 136 21.83 1 43 0 1
#> 60 13.15 1 38 1 0
#> 61 10.12 1 36 0 1
#> 60.1 13.15 1 38 1 0
#> 192 16.44 1 31 1 0
#> 70 7.38 1 30 1 0
#> 128.1 20.35 1 35 0 1
#> 63 22.77 1 31 1 0
#> 78 23.88 1 43 0 0
#> 97 19.14 1 65 0 1
#> 36 21.19 1 48 0 1
#> 111 17.45 1 47 0 1
#> 56 12.21 1 60 0 0
#> 169 22.41 1 46 0 0
#> 61.1 10.12 1 36 0 1
#> 167 15.55 1 56 1 0
#> 166 19.98 1 48 0 0
#> 168 23.72 1 70 0 0
#> 140.1 12.68 1 59 1 0
#> 86.1 23.81 1 58 0 1
#> 130.2 16.47 1 53 0 1
#> 90 20.94 1 50 0 1
#> 179.1 18.63 1 42 0 0
#> 15 22.68 1 48 0 0
#> 107.2 11.18 1 54 1 0
#> 171 16.57 1 41 0 1
#> 149 8.37 1 33 1 0
#> 110 17.56 1 65 0 1
#> 105.2 19.75 1 60 0 0
#> 88 18.37 1 47 0 0
#> 15.1 22.68 1 48 0 0
#> 6 15.64 1 39 0 0
#> 14 12.89 1 21 0 0
#> 18 15.21 1 49 1 0
#> 150 20.33 1 48 0 0
#> 188 16.16 1 46 0 1
#> 128.2 20.35 1 35 0 1
#> 125 15.65 1 67 1 0
#> 170 19.54 1 43 0 1
#> 124.1 9.73 1 NA 1 0
#> 49.2 12.19 1 48 1 0
#> 168.1 23.72 1 70 0 0
#> 183 9.24 1 67 1 0
#> 149.1 8.37 1 33 1 0
#> 110.1 17.56 1 65 0 1
#> 57.1 14.46 1 45 0 1
#> 37 12.52 1 57 1 0
#> 110.2 17.56 1 65 0 1
#> 92 22.92 1 47 0 1
#> 76 19.22 1 54 0 1
#> 89 11.44 1 NA 0 0
#> 130.3 16.47 1 53 0 1
#> 13.2 14.34 1 54 0 1
#> 168.2 23.72 1 70 0 0
#> 158.1 20.14 1 74 1 0
#> 179.2 18.63 1 42 0 0
#> 39 15.59 1 37 0 1
#> 167.1 15.55 1 56 1 0
#> 6.1 15.64 1 39 0 0
#> 56.1 12.21 1 60 0 0
#> 60.2 13.15 1 38 1 0
#> 69 23.23 1 25 0 1
#> 97.1 19.14 1 65 0 1
#> 86.2 23.81 1 58 0 1
#> 77 7.27 1 67 0 1
#> 184 17.77 1 38 0 0
#> 54 24.00 0 53 1 0
#> 152 24.00 0 36 0 1
#> 185 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 116 24.00 0 58 0 1
#> 120 24.00 0 68 0 1
#> 186 24.00 0 45 1 0
#> 74 24.00 0 43 0 1
#> 120.1 24.00 0 68 0 1
#> 135 24.00 0 58 1 0
#> 94 24.00 0 51 0 1
#> 73 24.00 0 NA 0 1
#> 9 24.00 0 31 1 0
#> 73.1 24.00 0 NA 0 1
#> 138 24.00 0 44 1 0
#> 152.1 24.00 0 36 0 1
#> 156 24.00 0 50 1 0
#> 31 24.00 0 36 0 1
#> 71 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 72 24.00 0 40 0 1
#> 17 24.00 0 38 0 1
#> 19 24.00 0 57 0 1
#> 173 24.00 0 19 0 1
#> 118 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 116.1 24.00 0 58 0 1
#> 122 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 17.1 24.00 0 38 0 1
#> 94.1 24.00 0 51 0 1
#> 182 24.00 0 35 0 0
#> 186.1 24.00 0 45 1 0
#> 9.1 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 7 24.00 0 37 1 0
#> 116.2 24.00 0 58 0 1
#> 160 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 38 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 141 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 138.1 24.00 0 44 1 0
#> 17.2 24.00 0 38 0 1
#> 196 24.00 0 19 0 0
#> 73.2 24.00 0 NA 0 1
#> 135.1 24.00 0 58 1 0
#> 161 24.00 0 45 0 0
#> 137 24.00 0 45 1 0
#> 62 24.00 0 71 0 0
#> 1 24.00 0 23 1 0
#> 47 24.00 0 38 0 1
#> 165 24.00 0 47 0 0
#> 143 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 137.1 24.00 0 45 1 0
#> 95 24.00 0 68 0 1
#> 103 24.00 0 56 1 0
#> 132 24.00 0 55 0 0
#> 44.1 24.00 0 56 0 0
#> 72.1 24.00 0 40 0 1
#> 47.1 24.00 0 38 0 1
#> 162 24.00 0 51 0 0
#> 182.1 24.00 0 35 0 0
#> 119 24.00 0 17 0 0
#> 135.2 24.00 0 58 1 0
#> 141.1 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 82.1 24.00 0 34 0 0
#> 72.2 24.00 0 40 0 1
#> 94.2 24.00 0 51 0 1
#> 151.1 24.00 0 42 0 0
#> 104 24.00 0 50 1 0
#> 178 24.00 0 52 1 0
#> 174 24.00 0 49 1 0
#> 74.1 24.00 0 43 0 1
#> 12.1 24.00 0 63 0 0
#> 104.1 24.00 0 50 1 0
#> 135.3 24.00 0 58 1 0
#> 94.3 24.00 0 51 0 1
#> 186.2 24.00 0 45 1 0
#> 141.2 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 148 24.00 0 61 1 0
#> 3 24.00 0 31 1 0
#> 95.1 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.503 NA NA NA
#> 2 age, Cure model 0.0164 NA NA NA
#> 3 grade_ii, Cure model -0.279 NA NA NA
#> 4 grade_iii, Cure model 0.124 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00911 NA NA NA
#> 2 grade_ii, Survival model 1.17 NA NA NA
#> 3 grade_iii, Survival model 0.144 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.5028 0.0164 -0.2789 0.1240
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.5
#> Residual Deviance: 259.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.50276845 0.01639735 -0.27893393 0.12400950
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00910622 1.17469684 0.14366265
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.115955631 0.440264414 0.786942572 0.717840164 0.061553870 0.595146915
#> [7] 0.512912239 0.061553870 0.888650486 0.512912239 0.512912239 0.574333367
#> [13] 0.747965931 0.368374981 0.115955631 0.316047818 0.697861484 0.144299725
#> [19] 0.419243599 0.983628825 0.667801518 0.553691769 0.852706167 0.806098463
#> [25] 0.717840164 0.275425669 0.888650486 0.209666848 0.237140477 0.357958606
#> [31] 0.172275439 0.983628825 0.687866966 0.879571198 0.471640506 0.932428907
#> [37] 0.852706167 0.471640506 0.450881376 0.007103405 0.574333367 0.237140477
#> [43] 0.134519464 0.758182800 0.914832886 0.758182800 0.512912239 0.966829186
#> [49] 0.172275439 0.080527209 0.001618139 0.295609155 0.153481867 0.429722192
#> [55] 0.834056435 0.106559937 0.914832886 0.647503502 0.227767952 0.021416796
#> [61] 0.806098463 0.007103405 0.471640506 0.162805991 0.316047818 0.089100179
#> [67] 0.888650486 0.461236969 0.949915515 0.388653272 0.237140477 0.347149449
#> [73] 0.089100179 0.616105315 0.796510494 0.677913815 0.199849232 0.563989846
#> [79] 0.172275439 0.605694886 0.265525011 0.852706167 0.021416796 0.941203022
#> [85] 0.949915515 0.388653272 0.697861484 0.824766794 0.388653272 0.052069754
#> [91] 0.285464965 0.471640506 0.717840164 0.021416796 0.209666848 0.316047818
#> [97] 0.636959200 0.647503502 0.616105315 0.834056435 0.758182800 0.042997884
#> [103] 0.295609155 0.007103405 0.975215520 0.378474394 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 194 45 123 13 113 26 85 113.1 107 85.1 85.2 100 81
#> 22.40 17.42 13.00 14.34 22.86 15.77 16.44 22.86 11.18 16.44 16.44 16.07 14.06
#> 134 194.1 179 57 153 117 25 29 79 49 140 13.1 55
#> 17.81 22.40 18.63 14.46 21.33 17.46 6.32 15.45 16.23 12.19 12.68 14.34 19.34
#> 107.1 158 105 41 128 25.1 180 43 130 145 49.1 130.1 106
#> 11.18 20.14 19.75 18.02 20.35 6.32 14.82 12.10 16.47 10.07 12.19 16.47 16.67
#> 86 100.1 105.1 136 60 61 60.1 192 70 128.1 63 78 97
#> 23.81 16.07 19.75 21.83 13.15 10.12 13.15 16.44 7.38 20.35 22.77 23.88 19.14
#> 36 111 56 169 61.1 167 166 168 140.1 86.1 130.2 90 179.1
#> 21.19 17.45 12.21 22.41 10.12 15.55 19.98 23.72 12.68 23.81 16.47 20.94 18.63
#> 15 107.2 171 149 110 105.2 88 15.1 6 14 18 150 188
#> 22.68 11.18 16.57 8.37 17.56 19.75 18.37 22.68 15.64 12.89 15.21 20.33 16.16
#> 128.2 125 170 49.2 168.1 183 149.1 110.1 57.1 37 110.2 92 76
#> 20.35 15.65 19.54 12.19 23.72 9.24 8.37 17.56 14.46 12.52 17.56 22.92 19.22
#> 130.3 13.2 168.2 158.1 179.2 39 167.1 6.1 56.1 60.2 69 97.1 86.2
#> 16.47 14.34 23.72 20.14 18.63 15.59 15.55 15.64 12.21 13.15 23.23 19.14 23.81
#> 77 184 54 152 185 121 116 120 186 74 120.1 135 94
#> 7.27 17.77 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 138 152.1 156 31 71 12 72 17 19 173 118 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 116.1 122 87 17.1 94.1 182 186.1 9.1 82 7 116.2 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 38 112 141 28 138.1 17.2 196 135.1 161 137 62 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 165 143 67 137.1 95 103 132 44.1 72.1 47.1 162 182.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 135.2 141.1 151 82.1 72.2 94.2 151.1 104 178 174 74.1 12.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.1 135.3 94.3 186.2 141.2 80 148 3 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[68]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005234685 0.395833677 0.336948930
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.64502811 0.02706474 0.39588523
#> grade_iii, Cure model
#> 0.96671236
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 183 9.24 1 67 1 0
#> 88 18.37 1 47 0 0
#> 117 17.46 1 26 0 1
#> 180 14.82 1 37 0 0
#> 89 11.44 1 NA 0 0
#> 155 13.08 1 26 0 0
#> 4 17.64 1 NA 0 1
#> 125 15.65 1 67 1 0
#> 180.1 14.82 1 37 0 0
#> 158 20.14 1 74 1 0
#> 58 19.34 1 39 0 0
#> 96 14.54 1 33 0 1
#> 59 10.16 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 108 18.29 1 39 0 1
#> 60 13.15 1 38 1 0
#> 92 22.92 1 47 0 1
#> 77 7.27 1 67 0 1
#> 97 19.14 1 65 0 1
#> 171 16.57 1 41 0 1
#> 106 16.67 1 49 1 0
#> 101 9.97 1 10 0 1
#> 190 20.81 1 42 1 0
#> 114 13.68 1 NA 0 0
#> 91 5.33 1 61 0 1
#> 13 14.34 1 54 0 1
#> 78 23.88 1 43 0 0
#> 69 23.23 1 25 0 1
#> 36 21.19 1 48 0 1
#> 100 16.07 1 60 0 0
#> 114.1 13.68 1 NA 0 0
#> 166 19.98 1 48 0 0
#> 100.1 16.07 1 60 0 0
#> 117.1 17.46 1 26 0 1
#> 127 3.53 1 62 0 1
#> 39 15.59 1 37 0 1
#> 139 21.49 1 63 1 0
#> 92.1 22.92 1 47 0 1
#> 57 14.46 1 45 0 1
#> 183.1 9.24 1 67 1 0
#> 190.1 20.81 1 42 1 0
#> 195 11.76 1 NA 1 0
#> 124 9.73 1 NA 1 0
#> 10 10.53 1 34 0 0
#> 97.1 19.14 1 65 0 1
#> 25 6.32 1 34 1 0
#> 77.1 7.27 1 67 0 1
#> 127.1 3.53 1 62 0 1
#> 79 16.23 1 54 1 0
#> 66 22.13 1 53 0 0
#> 79.1 16.23 1 54 1 0
#> 169 22.41 1 46 0 0
#> 159 10.55 1 50 0 1
#> 139.1 21.49 1 63 1 0
#> 42 12.43 1 49 0 1
#> 107 11.18 1 54 1 0
#> 195.1 11.76 1 NA 1 0
#> 4.1 17.64 1 NA 0 1
#> 86 23.81 1 58 0 1
#> 14 12.89 1 21 0 0
#> 4.2 17.64 1 NA 0 1
#> 133 14.65 1 57 0 0
#> 114.2 13.68 1 NA 0 0
#> 36.1 21.19 1 48 0 1
#> 97.2 19.14 1 65 0 1
#> 183.2 9.24 1 67 1 0
#> 129 23.41 1 53 1 0
#> 149 8.37 1 33 1 0
#> 181 16.46 1 45 0 1
#> 133.1 14.65 1 57 0 0
#> 117.2 17.46 1 26 0 1
#> 175 21.91 1 43 0 0
#> 107.1 11.18 1 54 1 0
#> 43 12.10 1 61 0 1
#> 106.1 16.67 1 49 1 0
#> 129.1 23.41 1 53 1 0
#> 183.3 9.24 1 67 1 0
#> 169.1 22.41 1 46 0 0
#> 36.2 21.19 1 48 0 1
#> 133.2 14.65 1 57 0 0
#> 199 19.81 1 NA 0 1
#> 139.2 21.49 1 63 1 0
#> 76 19.22 1 54 0 1
#> 16 8.71 1 71 0 1
#> 52 10.42 1 52 0 1
#> 164 23.60 1 76 0 1
#> 192 16.44 1 31 1 0
#> 49 12.19 1 48 1 0
#> 167 15.55 1 56 1 0
#> 55 19.34 1 69 0 1
#> 16.1 8.71 1 71 0 1
#> 159.1 10.55 1 50 0 1
#> 40 18.00 1 28 1 0
#> 60.1 13.15 1 38 1 0
#> 63 22.77 1 31 1 0
#> 199.1 19.81 1 NA 0 1
#> 42.1 12.43 1 49 0 1
#> 140 12.68 1 59 1 0
#> 106.2 16.67 1 49 1 0
#> 107.2 11.18 1 54 1 0
#> 23 16.92 1 61 0 0
#> 69.1 23.23 1 25 0 1
#> 127.2 3.53 1 62 0 1
#> 195.2 11.76 1 NA 1 0
#> 124.1 9.73 1 NA 1 0
#> 5 16.43 1 51 0 1
#> 114.3 13.68 1 NA 0 0
#> 70 7.38 1 30 1 0
#> 114.4 13.68 1 NA 0 0
#> 85 16.44 1 36 0 0
#> 150 20.33 1 48 0 0
#> 43.1 12.10 1 61 0 1
#> 121 24.00 0 57 1 0
#> 74 24.00 0 43 0 1
#> 193 24.00 0 45 0 1
#> 28 24.00 0 67 1 0
#> 54 24.00 0 53 1 0
#> 82 24.00 0 34 0 0
#> 161 24.00 0 45 0 0
#> 109 24.00 0 48 0 0
#> 71 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 82.1 24.00 0 34 0 0
#> 35 24.00 0 51 0 0
#> 174 24.00 0 49 1 0
#> 2 24.00 0 9 0 0
#> 141 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 34 24.00 0 36 0 0
#> 200 24.00 0 64 0 0
#> 83 24.00 0 6 0 0
#> 47 24.00 0 38 0 1
#> 147 24.00 0 76 1 0
#> 48 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 65 24.00 0 57 1 0
#> 74.1 24.00 0 43 0 1
#> 35.1 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 109.1 24.00 0 48 0 0
#> 27 24.00 0 63 1 0
#> 75 24.00 0 21 1 0
#> 46 24.00 0 71 0 0
#> 173 24.00 0 19 0 1
#> 53 24.00 0 32 0 1
#> 95 24.00 0 68 0 1
#> 53.1 24.00 0 32 0 1
#> 138 24.00 0 44 1 0
#> 35.2 24.00 0 51 0 0
#> 65.1 24.00 0 57 1 0
#> 28.1 24.00 0 67 1 0
#> 151 24.00 0 42 0 0
#> 67 24.00 0 25 0 0
#> 67.1 24.00 0 25 0 0
#> 33 24.00 0 53 0 0
#> 35.3 24.00 0 51 0 0
#> 193.1 24.00 0 45 0 1
#> 152 24.00 0 36 0 1
#> 71.1 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 118 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 191.1 24.00 0 60 0 1
#> 165 24.00 0 47 0 0
#> 115 24.00 0 NA 1 0
#> 178 24.00 0 52 1 0
#> 163.1 24.00 0 66 0 0
#> 193.2 24.00 0 45 0 1
#> 148 24.00 0 61 1 0
#> 3 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 174.1 24.00 0 49 1 0
#> 172 24.00 0 41 0 0
#> 112 24.00 0 61 0 0
#> 138.1 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 116 24.00 0 58 0 1
#> 7 24.00 0 37 1 0
#> 17 24.00 0 38 0 1
#> 72 24.00 0 40 0 1
#> 9 24.00 0 31 1 0
#> 141.1 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 83.1 24.00 0 6 0 0
#> 38.1 24.00 0 31 1 0
#> 74.2 24.00 0 43 0 1
#> 182 24.00 0 35 0 0
#> 109.2 24.00 0 48 0 0
#> 161.1 24.00 0 45 0 0
#> 31.1 24.00 0 36 0 1
#> 84.1 24.00 0 39 0 1
#> 148.1 24.00 0 61 1 0
#> 17.1 24.00 0 38 0 1
#> 75.1 24.00 0 21 1 0
#> 163.2 24.00 0 66 0 0
#> 71.2 24.00 0 51 0 0
#> 173.1 24.00 0 19 0 1
#> 118.1 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.65 NA NA NA
#> 2 age, Cure model 0.0271 NA NA NA
#> 3 grade_ii, Cure model 0.396 NA NA NA
#> 4 grade_iii, Cure model 0.967 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00523 NA NA NA
#> 2 grade_ii, Survival model 0.396 NA NA NA
#> 3 grade_iii, Survival model 0.337 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.64503 0.02706 0.39589 0.96671
#>
#> Degrees of Freedom: 181 Total (i.e. Null); 178 Residual
#> Null Deviance: 252
#> Residual Deviance: 238.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.64502811 0.02706474 0.39588523 0.96671236
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005234685 0.395833677 0.336948930
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.90649143 0.53368794 0.56199801 0.72043432 0.79555922 0.69696958
#> [7] 0.72043432 0.45335746 0.47472536 0.75841035 0.03521142 0.54324224
#> [13] 0.78095030 0.24698192 0.95729205 0.50539639 0.62322031 0.59769812
#> [19] 0.89983312 0.42039134 0.97585391 0.77349755 0.07991691 0.21313475
#> [25] 0.38643183 0.68107921 0.46407653 0.68107921 0.56199801 0.98199792
#> [31] 0.70486018 0.34990598 0.24698192 0.76598265 0.90649143 0.42039134
#> [37] 0.88642724 0.50539639 0.96967382 0.95729205 0.98199792 0.66505087
#> [43] 0.32121042 0.66505087 0.29260696 0.87301042 0.34990598 0.81746197
#> [49] 0.85270794 0.11975323 0.80288766 0.73577074 0.38643183 0.50539639
#> [55] 0.90649143 0.17577050 0.94467760 0.63175957 0.73577074 0.56199801
#> [61] 0.33563555 0.85270794 0.83879580 0.59769812 0.17577050 0.90649143
#> [67] 0.29260696 0.38643183 0.73577074 0.34990598 0.49522225 0.93200988
#> [73] 0.89315128 0.15054512 0.64021057 0.83170103 0.71268943 0.47472536
#> [79] 0.93200988 0.87301042 0.55267742 0.78095030 0.27752716 0.81746197
#> [85] 0.81020835 0.59769812 0.85270794 0.58870843 0.21313475 0.98199792
#> [91] 0.65679343 0.95100027 0.64021057 0.44232850 0.83879580 0.00000000
#> [97] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000
#>
#> $Time
#> 183 88 117 180 155 125 180.1 158 58 96 24 108 60
#> 9.24 18.37 17.46 14.82 13.08 15.65 14.82 20.14 19.34 14.54 23.89 18.29 13.15
#> 92 77 97 171 106 101 190 91 13 78 69 36 100
#> 22.92 7.27 19.14 16.57 16.67 9.97 20.81 5.33 14.34 23.88 23.23 21.19 16.07
#> 166 100.1 117.1 127 39 139 92.1 57 183.1 190.1 10 97.1 25
#> 19.98 16.07 17.46 3.53 15.59 21.49 22.92 14.46 9.24 20.81 10.53 19.14 6.32
#> 77.1 127.1 79 66 79.1 169 159 139.1 42 107 86 14 133
#> 7.27 3.53 16.23 22.13 16.23 22.41 10.55 21.49 12.43 11.18 23.81 12.89 14.65
#> 36.1 97.2 183.2 129 149 181 133.1 117.2 175 107.1 43 106.1 129.1
#> 21.19 19.14 9.24 23.41 8.37 16.46 14.65 17.46 21.91 11.18 12.10 16.67 23.41
#> 183.3 169.1 36.2 133.2 139.2 76 16 52 164 192 49 167 55
#> 9.24 22.41 21.19 14.65 21.49 19.22 8.71 10.42 23.60 16.44 12.19 15.55 19.34
#> 16.1 159.1 40 60.1 63 42.1 140 106.2 107.2 23 69.1 127.2 5
#> 8.71 10.55 18.00 13.15 22.77 12.43 12.68 16.67 11.18 16.92 23.23 3.53 16.43
#> 70 85 150 43.1 121 74 193 28 54 82 161 109 71
#> 7.38 16.44 20.33 12.10 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 82.1 35 174 2 141 163 34 200 83 47 147 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 65 74.1 35.1 191 109.1 27 75 46 173 53 95 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 35.2 65.1 28.1 151 67 67.1 33 35.3 193.1 152 71.1 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 118 1 191.1 165 178 163.1 193.2 148 3 98 174.1 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 138.1 135 116 7 17 72 9 141.1 119 83.1 38.1 74.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 109.2 161.1 31.1 84.1 148.1 17.1 75.1 163.2 71.2 173.1 118.1 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[69]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003478708 0.588271748 0.124847511
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.1780673422 0.0004246388 0.3395059595
#> grade_iii, Cure model
#> 0.6212348752
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 157 15.10 1 47 0 0
#> 114 13.68 1 NA 0 0
#> 167 15.55 1 56 1 0
#> 56 12.21 1 60 0 0
#> 15 22.68 1 48 0 0
#> 91 5.33 1 61 0 1
#> 92 22.92 1 47 0 1
#> 187 9.92 1 39 1 0
#> 190 20.81 1 42 1 0
#> 106 16.67 1 49 1 0
#> 170 19.54 1 43 0 1
#> 51 18.23 1 83 0 1
#> 99 21.19 1 38 0 1
#> 55 19.34 1 69 0 1
#> 167.1 15.55 1 56 1 0
#> 60 13.15 1 38 1 0
#> 42 12.43 1 49 0 1
#> 190.1 20.81 1 42 1 0
#> 184 17.77 1 38 0 0
#> 168 23.72 1 70 0 0
#> 16 8.71 1 71 0 1
#> 179 18.63 1 42 0 0
#> 41 18.02 1 40 1 0
#> 169 22.41 1 46 0 0
#> 114.1 13.68 1 NA 0 0
#> 97 19.14 1 65 0 1
#> 157.1 15.10 1 47 0 0
#> 179.1 18.63 1 42 0 0
#> 89 11.44 1 NA 0 0
#> 110 17.56 1 65 0 1
#> 180 14.82 1 37 0 0
#> 194 22.40 1 38 0 1
#> 57 14.46 1 45 0 1
#> 99.1 21.19 1 38 0 1
#> 105 19.75 1 60 0 0
#> 40 18.00 1 28 1 0
#> 39 15.59 1 37 0 1
#> 130 16.47 1 53 0 1
#> 110.1 17.56 1 65 0 1
#> 59 10.16 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 97.1 19.14 1 65 0 1
#> 124 9.73 1 NA 1 0
#> 179.2 18.63 1 42 0 0
#> 49 12.19 1 48 1 0
#> 167.2 15.55 1 56 1 0
#> 6 15.64 1 39 0 0
#> 177 12.53 1 75 0 0
#> 195 11.76 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 184.1 17.77 1 38 0 0
#> 183 9.24 1 67 1 0
#> 128 20.35 1 35 0 1
#> 145 10.07 1 65 1 0
#> 171 16.57 1 41 0 1
#> 114.2 13.68 1 NA 0 0
#> 61 10.12 1 36 0 1
#> 134 17.81 1 47 1 0
#> 32 20.90 1 37 1 0
#> 154 12.63 1 20 1 0
#> 125 15.65 1 67 1 0
#> 179.3 18.63 1 42 0 0
#> 92.1 22.92 1 47 0 1
#> 153 21.33 1 55 1 0
#> 149 8.37 1 33 1 0
#> 187.1 9.92 1 39 1 0
#> 195.1 11.76 1 NA 1 0
#> 78.1 23.88 1 43 0 0
#> 177.1 12.53 1 75 0 0
#> 127 3.53 1 62 0 1
#> 149.1 8.37 1 33 1 0
#> 89.1 11.44 1 NA 0 0
#> 158 20.14 1 74 1 0
#> 114.3 13.68 1 NA 0 0
#> 51.1 18.23 1 83 0 1
#> 43 12.10 1 61 0 1
#> 194.1 22.40 1 38 0 1
#> 51.2 18.23 1 83 0 1
#> 192 16.44 1 31 1 0
#> 6.1 15.64 1 39 0 0
#> 8 18.43 1 32 0 0
#> 184.2 17.77 1 38 0 0
#> 32.1 20.90 1 37 1 0
#> 194.2 22.40 1 38 0 1
#> 50 10.02 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 29 15.45 1 68 1 0
#> 155 13.08 1 26 0 0
#> 170.1 19.54 1 43 0 1
#> 25 6.32 1 34 1 0
#> 128.1 20.35 1 35 0 1
#> 106.1 16.67 1 49 1 0
#> 153.1 21.33 1 55 1 0
#> 125.1 15.65 1 67 1 0
#> 90 20.94 1 50 0 1
#> 155.1 13.08 1 26 0 0
#> 61.1 10.12 1 36 0 1
#> 45 17.42 1 54 0 1
#> 155.2 13.08 1 26 0 0
#> 190.2 20.81 1 42 1 0
#> 70 7.38 1 30 1 0
#> 60.1 13.15 1 38 1 0
#> 125.2 15.65 1 67 1 0
#> 167.3 15.55 1 56 1 0
#> 63 22.77 1 31 1 0
#> 55.1 19.34 1 69 0 1
#> 168.1 23.72 1 70 0 0
#> 184.3 17.77 1 38 0 0
#> 60.2 13.15 1 38 1 0
#> 181 16.46 1 45 0 1
#> 6.2 15.64 1 39 0 0
#> 69 23.23 1 25 0 1
#> 62 24.00 0 71 0 0
#> 137 24.00 0 45 1 0
#> 54 24.00 0 53 1 0
#> 144 24.00 0 28 0 1
#> 173 24.00 0 19 0 1
#> 103 24.00 0 56 1 0
#> 115 24.00 0 NA 1 0
#> 54.1 24.00 0 53 1 0
#> 182 24.00 0 35 0 0
#> 67 24.00 0 25 0 0
#> 84 24.00 0 39 0 1
#> 116 24.00 0 58 0 1
#> 174 24.00 0 49 1 0
#> 165 24.00 0 47 0 0
#> 147 24.00 0 76 1 0
#> 3 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 176 24.00 0 43 0 1
#> 142 24.00 0 53 0 0
#> 82 24.00 0 34 0 0
#> 156 24.00 0 50 1 0
#> 95 24.00 0 68 0 1
#> 53 24.00 0 32 0 1
#> 95.1 24.00 0 68 0 1
#> 2 24.00 0 9 0 0
#> 33 24.00 0 53 0 0
#> 11 24.00 0 42 0 1
#> 2.1 24.00 0 9 0 0
#> 191 24.00 0 60 0 1
#> 121 24.00 0 57 1 0
#> 28 24.00 0 67 1 0
#> 2.2 24.00 0 9 0 0
#> 67.1 24.00 0 25 0 0
#> 72 24.00 0 40 0 1
#> 3.1 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 137.1 24.00 0 45 1 0
#> 73 24.00 0 NA 0 1
#> 148 24.00 0 61 1 0
#> 191.1 24.00 0 60 0 1
#> 27 24.00 0 63 1 0
#> 19 24.00 0 57 0 1
#> 109 24.00 0 48 0 0
#> 172 24.00 0 41 0 0
#> 44 24.00 0 56 0 0
#> 162 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 121.1 24.00 0 57 1 0
#> 176.1 24.00 0 43 0 1
#> 182.1 24.00 0 35 0 0
#> 11.1 24.00 0 42 0 1
#> 147.1 24.00 0 76 1 0
#> 28.1 24.00 0 67 1 0
#> 84.1 24.00 0 39 0 1
#> 163 24.00 0 66 0 0
#> 102 24.00 0 49 0 0
#> 94 24.00 0 51 0 1
#> 31 24.00 0 36 0 1
#> 35 24.00 0 51 0 0
#> 35.1 24.00 0 51 0 0
#> 109.1 24.00 0 48 0 0
#> 74 24.00 0 43 0 1
#> 47 24.00 0 38 0 1
#> 141 24.00 0 44 1 0
#> 137.2 24.00 0 45 1 0
#> 46 24.00 0 71 0 0
#> 28.2 24.00 0 67 1 0
#> 160 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 33.1 24.00 0 53 0 0
#> 174.1 24.00 0 49 1 0
#> 147.2 24.00 0 76 1 0
#> 132 24.00 0 55 0 0
#> 132.1 24.00 0 55 0 0
#> 182.2 24.00 0 35 0 0
#> 65 24.00 0 57 1 0
#> 12 24.00 0 63 0 0
#> 165.1 24.00 0 47 0 0
#> 135.1 24.00 0 58 1 0
#> 120 24.00 0 68 0 1
#> 21 24.00 0 47 0 0
#> 44.1 24.00 0 56 0 0
#> 172.1 24.00 0 41 0 0
#> 94.1 24.00 0 51 0 1
#> 160.1 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.178 NA NA NA
#> 2 age, Cure model 0.000425 NA NA NA
#> 3 grade_ii, Cure model 0.340 NA NA NA
#> 4 grade_iii, Cure model 0.621 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00348 NA NA NA
#> 2 grade_ii, Survival model 0.588 NA NA NA
#> 3 grade_iii, Survival model 0.125 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.1780673 0.0004246 0.3395060 0.6212349
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 253.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.1780673422 0.0004246388 0.3395059595 0.6212348752
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003478708 0.588271748 0.124847511
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.79700753 0.76082581 0.89496476 0.19253524 0.98735743 0.13973163
#> [7] 0.93559715 0.35806925 0.64974425 0.43085077 0.53587290 0.29582607
#> [13] 0.45069479 0.76082581 0.82580353 0.88808527 0.35806925 0.58997237
#> [19] 0.07870686 0.95528587 0.48929544 0.56315124 0.20931665 0.47016158
#> [25] 0.79700753 0.48929544 0.62408413 0.81139250 0.22586860 0.81860832
#> [31] 0.29582607 0.42066197 0.57223542 0.75313445 0.67454942 0.62408413
#> [37] 0.47016158 0.48929544 0.90183200 0.76082581 0.73022840 0.87434316
#> [43] 0.03327028 0.58997237 0.94874628 0.38949292 0.92889895 0.66626758
#> [49] 0.91542911 0.58117972 0.33452942 0.86741228 0.70721753 0.48929544
#> [55] 0.13973163 0.26940805 0.96180535 0.93559715 0.03327028 0.87434316
#> [61] 0.99368687 0.96180535 0.41041557 0.53587290 0.90864075 0.22586860
#> [67] 0.53587290 0.69100753 0.73022840 0.52636931 0.58997237 0.33452942
#> [73] 0.22586860 0.69912343 0.78975896 0.84663209 0.43085077 0.98101168
#> [79] 0.38949292 0.64974425 0.26940805 0.70721753 0.32157215 0.84663209
#> [85] 0.91542911 0.64118050 0.84663209 0.35806925 0.97462350 0.82580353
#> [91] 0.70721753 0.76082581 0.17548490 0.45069479 0.07870686 0.58997237
#> [97] 0.82580353 0.68279459 0.73022840 0.11863590 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 157 167 56 15 91 92 187 190 106 170 51 99 55
#> 15.10 15.55 12.21 22.68 5.33 22.92 9.92 20.81 16.67 19.54 18.23 21.19 19.34
#> 167.1 60 42 190.1 184 168 16 179 41 169 97 157.1 179.1
#> 15.55 13.15 12.43 20.81 17.77 23.72 8.71 18.63 18.02 22.41 19.14 15.10 18.63
#> 110 180 194 57 99.1 105 40 39 130 110.1 97.1 179.2 49
#> 17.56 14.82 22.40 14.46 21.19 19.75 18.00 15.59 16.47 17.56 19.14 18.63 12.19
#> 167.2 6 177 78 184.1 183 128 145 171 61 134 32 154
#> 15.55 15.64 12.53 23.88 17.77 9.24 20.35 10.07 16.57 10.12 17.81 20.90 12.63
#> 125 179.3 92.1 153 149 187.1 78.1 177.1 127 149.1 158 51.1 43
#> 15.65 18.63 22.92 21.33 8.37 9.92 23.88 12.53 3.53 8.37 20.14 18.23 12.10
#> 194.1 51.2 192 6.1 8 184.2 32.1 194.2 100 29 155 170.1 25
#> 22.40 18.23 16.44 15.64 18.43 17.77 20.90 22.40 16.07 15.45 13.08 19.54 6.32
#> 128.1 106.1 153.1 125.1 90 155.1 61.1 45 155.2 190.2 70 60.1 125.2
#> 20.35 16.67 21.33 15.65 20.94 13.08 10.12 17.42 13.08 20.81 7.38 13.15 15.65
#> 167.3 63 55.1 168.1 184.3 60.2 181 6.2 69 62 137 54 144
#> 15.55 22.77 19.34 23.72 17.77 13.15 16.46 15.64 23.23 24.00 24.00 24.00 24.00
#> 173 103 54.1 182 67 84 116 174 165 147 3 138 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 142 82 156 95 53 95.1 2 33 11 2.1 191 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 2.2 67.1 72 3.1 131 137.1 148 191.1 27 19 109 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 162 135 121.1 176.1 182.1 11.1 147.1 28.1 84.1 163 102 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 35 35.1 109.1 74 47 141 137.2 46 28.2 160 196 33.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174.1 147.2 132 132.1 182.2 65 12 165.1 135.1 120 21 44.1 172.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 160.1 38 185
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[70]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01420598 0.35803183 0.11656756
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.83951664 0.01437989 0.43071932
#> grade_iii, Cure model
#> 0.68045913
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 61 10.12 1 36 0 1
#> 26 15.77 1 49 0 1
#> 39 15.59 1 37 0 1
#> 70 7.38 1 30 1 0
#> 23 16.92 1 61 0 0
#> 5 16.43 1 51 0 1
#> 139 21.49 1 63 1 0
#> 100 16.07 1 60 0 0
#> 42 12.43 1 49 0 1
#> 5.1 16.43 1 51 0 1
#> 37 12.52 1 57 1 0
#> 37.1 12.52 1 57 1 0
#> 56 12.21 1 60 0 0
#> 25 6.32 1 34 1 0
#> 93 10.33 1 52 0 1
#> 140 12.68 1 59 1 0
#> 88 18.37 1 47 0 0
#> 63 22.77 1 31 1 0
#> 68 20.62 1 44 0 0
#> 123 13.00 1 44 1 0
#> 4 17.64 1 NA 0 1
#> 88.1 18.37 1 47 0 0
#> 157 15.10 1 47 0 0
#> 58 19.34 1 39 0 0
#> 150 20.33 1 48 0 0
#> 66 22.13 1 53 0 0
#> 101 9.97 1 10 0 1
#> 16 8.71 1 71 0 1
#> 155 13.08 1 26 0 0
#> 25.1 6.32 1 34 1 0
#> 85 16.44 1 36 0 0
#> 164 23.60 1 76 0 1
#> 106 16.67 1 49 1 0
#> 106.1 16.67 1 49 1 0
#> 70.1 7.38 1 30 1 0
#> 127 3.53 1 62 0 1
#> 96 14.54 1 33 0 1
#> 158 20.14 1 74 1 0
#> 79 16.23 1 54 1 0
#> 155.1 13.08 1 26 0 0
#> 189 10.51 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 36 21.19 1 48 0 1
#> 29 15.45 1 68 1 0
#> 113 22.86 1 34 0 0
#> 149 8.37 1 33 1 0
#> 149.1 8.37 1 33 1 0
#> 195 11.76 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 69 23.23 1 25 0 1
#> 105 19.75 1 60 0 0
#> 181 16.46 1 45 0 1
#> 117 17.46 1 26 0 1
#> 26.1 15.77 1 49 0 1
#> 128 20.35 1 35 0 1
#> 77 7.27 1 67 0 1
#> 5.2 16.43 1 51 0 1
#> 195.1 11.76 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 108 18.29 1 39 0 1
#> 52 10.42 1 52 0 1
#> 42.1 12.43 1 49 0 1
#> 155.2 13.08 1 26 0 0
#> 106.2 16.67 1 49 1 0
#> 197 21.60 1 69 1 0
#> 55 19.34 1 69 0 1
#> 81 14.06 1 34 0 0
#> 192 16.44 1 31 1 0
#> 96.1 14.54 1 33 0 1
#> 10 10.53 1 34 0 0
#> 123.1 13.00 1 44 1 0
#> 170 19.54 1 43 0 1
#> 153 21.33 1 55 1 0
#> 177 12.53 1 75 0 0
#> 183 9.24 1 67 1 0
#> 199 19.81 1 NA 0 1
#> 197.1 21.60 1 69 1 0
#> 170.1 19.54 1 43 0 1
#> 187 9.92 1 39 1 0
#> 189.1 10.51 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 37.2 12.52 1 57 1 0
#> 29.1 15.45 1 68 1 0
#> 197.2 21.60 1 69 1 0
#> 187.1 9.92 1 39 1 0
#> 100.1 16.07 1 60 0 0
#> 56.1 12.21 1 60 0 0
#> 66.1 22.13 1 53 0 0
#> 117.1 17.46 1 26 0 1
#> 81.1 14.06 1 34 0 0
#> 92 22.92 1 47 0 1
#> 181.1 16.46 1 45 0 1
#> 60 13.15 1 38 1 0
#> 194 22.40 1 38 0 1
#> 91 5.33 1 61 0 1
#> 45 17.42 1 54 0 1
#> 85.1 16.44 1 36 0 0
#> 128.1 20.35 1 35 0 1
#> 43 12.10 1 61 0 1
#> 29.2 15.45 1 68 1 0
#> 145 10.07 1 65 1 0
#> 123.2 13.00 1 44 1 0
#> 129 23.41 1 53 1 0
#> 153.1 21.33 1 55 1 0
#> 79.1 16.23 1 54 1 0
#> 70.2 7.38 1 30 1 0
#> 153.2 21.33 1 55 1 0
#> 77.1 7.27 1 67 0 1
#> 39.1 15.59 1 37 0 1
#> 166 19.98 1 48 0 0
#> 105.1 19.75 1 60 0 0
#> 68.1 20.62 1 44 0 0
#> 116 24.00 0 58 0 1
#> 67 24.00 0 25 0 0
#> 161 24.00 0 45 0 0
#> 19 24.00 0 57 0 1
#> 141 24.00 0 44 1 0
#> 19.1 24.00 0 57 0 1
#> 142 24.00 0 53 0 0
#> 103 24.00 0 56 1 0
#> 35 24.00 0 51 0 0
#> 33 24.00 0 53 0 0
#> 73 24.00 0 NA 0 1
#> 172 24.00 0 41 0 0
#> 21 24.00 0 47 0 0
#> 72 24.00 0 40 0 1
#> 44 24.00 0 56 0 0
#> 98 24.00 0 34 1 0
#> 200 24.00 0 64 0 0
#> 186 24.00 0 45 1 0
#> 118 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 116.1 24.00 0 58 0 1
#> 186.1 24.00 0 45 1 0
#> 47 24.00 0 38 0 1
#> 142.1 24.00 0 53 0 0
#> 3 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 17 24.00 0 38 0 1
#> 182 24.00 0 35 0 0
#> 132 24.00 0 55 0 0
#> 84 24.00 0 39 0 1
#> 174 24.00 0 49 1 0
#> 74 24.00 0 43 0 1
#> 161.1 24.00 0 45 0 0
#> 176 24.00 0 43 0 1
#> 27 24.00 0 63 1 0
#> 17.1 24.00 0 38 0 1
#> 142.2 24.00 0 53 0 0
#> 103.1 24.00 0 56 1 0
#> 75 24.00 0 21 1 0
#> 120 24.00 0 68 0 1
#> 182.1 24.00 0 35 0 0
#> 82 24.00 0 34 0 0
#> 54 24.00 0 53 1 0
#> 64 24.00 0 43 0 0
#> 71 24.00 0 51 0 0
#> 112 24.00 0 61 0 0
#> 67.1 24.00 0 25 0 0
#> 28 24.00 0 67 1 0
#> 71.1 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#> 75.1 24.00 0 21 1 0
#> 156 24.00 0 50 1 0
#> 178 24.00 0 52 1 0
#> 9 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 46 24.00 0 71 0 0
#> 9.1 24.00 0 31 1 0
#> 35.1 24.00 0 51 0 0
#> 9.2 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 137 24.00 0 45 1 0
#> 82.1 24.00 0 34 0 0
#> 33.1 24.00 0 53 0 0
#> 1 24.00 0 23 1 0
#> 53.1 24.00 0 32 0 1
#> 3.1 24.00 0 31 1 0
#> 3.2 24.00 0 31 1 0
#> 3.3 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 65 24.00 0 57 1 0
#> 135 24.00 0 58 1 0
#> 67.2 24.00 0 25 0 0
#> 176.1 24.00 0 43 0 1
#> 152 24.00 0 36 0 1
#> 138 24.00 0 44 1 0
#> 21.1 24.00 0 47 0 0
#> 54.1 24.00 0 53 1 0
#> 120.1 24.00 0 68 0 1
#> 143 24.00 0 51 0 0
#> 53.2 24.00 0 32 0 1
#> 98.1 24.00 0 34 1 0
#> 53.3 24.00 0 32 0 1
#> 116.2 24.00 0 58 0 1
#> 47.1 24.00 0 38 0 1
#> 122 24.00 0 66 0 0
#> 65.1 24.00 0 57 1 0
#> 71.2 24.00 0 51 0 0
#> 142.3 24.00 0 53 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.840 NA NA NA
#> 2 age, Cure model 0.0144 NA NA NA
#> 3 grade_ii, Cure model 0.431 NA NA NA
#> 4 grade_iii, Cure model 0.680 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0142 NA NA NA
#> 2 grade_ii, Survival model 0.358 NA NA NA
#> 3 grade_iii, Survival model 0.117 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.83952 0.01438 0.43072 0.68046
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 260.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.83951664 0.01437989 0.43071932 0.68045913
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01420598 0.35803183 0.11656756
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 7.399234e-01 3.415313e-01 3.623944e-01 8.679603e-01 1.945824e-01
#> [6] 2.732917e-01 3.203174e-02 3.212143e-01 6.323495e-01 2.732917e-01
#> [11] 5.944306e-01 5.944306e-01 6.583504e-01 9.403595e-01 7.260023e-01
#> [16] 5.693694e-01 1.391927e-01 9.965831e-03 5.858832e-02 5.331477e-01
#> [21] 1.391927e-01 4.163561e-01 1.247237e-01 7.984481e-02 1.534768e-02
#> [26] 7.680509e-01 8.246824e-01 4.974945e-01 9.403595e-01 2.462521e-01
#> [31] 4.331389e-04 2.030968e-01 2.030968e-01 8.679603e-01 9.848799e-01
#> [36] 4.391656e-01 8.569296e-02 3.016088e-01 4.974945e-01 5.358573e-02
#> [41] 4.878403e-02 3.836689e-01 7.430524e-03 8.391571e-01 8.391571e-01
#> [46] 4.276987e-01 3.304417e-03 9.800692e-02 2.284642e-01 1.703726e-01
#> [51] 3.415313e-01 6.895631e-02 9.109448e-01 2.732917e-01 2.901772e-05
#> [56] 1.544342e-01 7.122038e-01 6.323495e-01 4.974945e-01 2.030968e-01
#> [61] 2.151093e-02 1.247237e-01 4.621519e-01 2.462521e-01 4.391656e-01
#> [66] 6.985280e-01 5.331477e-01 1.110516e-01 3.623023e-02 5.818116e-01
#> [71] 8.103561e-01 2.151093e-02 1.110516e-01 7.821778e-01 1.623958e-01
#> [76] 5.944306e-01 3.836689e-01 2.151093e-02 7.821778e-01 3.212143e-01
#> [81] 6.583504e-01 1.534768e-02 1.703726e-01 4.621519e-01 5.191923e-03
#> [86] 2.284642e-01 4.855848e-01 1.255666e-02 9.698828e-01 1.862786e-01
#> [91] 2.462521e-01 6.895631e-02 6.849540e-01 3.836689e-01 7.539305e-01
#> [96] 5.331477e-01 1.638379e-03 3.623023e-02 3.016088e-01 8.679603e-01
#> [101] 3.623023e-02 9.109448e-01 3.623944e-01 9.174780e-02 9.800692e-02
#> [106] 5.858832e-02 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 61 26 39 70 23 5 139 100 42 5.1 37 37.1 56
#> 10.12 15.77 15.59 7.38 16.92 16.43 21.49 16.07 12.43 16.43 12.52 12.52 12.21
#> 25 93 140 88 63 68 123 88.1 157 58 150 66 101
#> 6.32 10.33 12.68 18.37 22.77 20.62 13.00 18.37 15.10 19.34 20.33 22.13 9.97
#> 16 155 25.1 85 164 106 106.1 70.1 127 96 158 79 155.1
#> 8.71 13.08 6.32 16.44 23.60 16.67 16.67 7.38 3.53 14.54 20.14 16.23 13.08
#> 90 36 29 113 149 149.1 180 69 105 181 117 26.1 128
#> 20.94 21.19 15.45 22.86 8.37 8.37 14.82 23.23 19.75 16.46 17.46 15.77 20.35
#> 77 5.2 168 108 52 42.1 155.2 106.2 197 55 81 192 96.1
#> 7.27 16.43 23.72 18.29 10.42 12.43 13.08 16.67 21.60 19.34 14.06 16.44 14.54
#> 10 123.1 170 153 177 183 197.1 170.1 187 40 37.2 29.1 197.2
#> 10.53 13.00 19.54 21.33 12.53 9.24 21.60 19.54 9.92 18.00 12.52 15.45 21.60
#> 187.1 100.1 56.1 66.1 117.1 81.1 92 181.1 60 194 91 45 85.1
#> 9.92 16.07 12.21 22.13 17.46 14.06 22.92 16.46 13.15 22.40 5.33 17.42 16.44
#> 128.1 43 29.2 145 123.2 129 153.1 79.1 70.2 153.2 77.1 39.1 166
#> 20.35 12.10 15.45 10.07 13.00 23.41 21.33 16.23 7.38 21.33 7.27 15.59 19.98
#> 105.1 68.1 116 67 161 19 141 19.1 142 103 35 33 172
#> 19.75 20.62 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 72 44 98 200 186 118 109 116.1 186.1 47 142.1 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 17 182 132 84 174 74 161.1 176 27 17.1 142.2 103.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 120 182.1 82 54 64 71 112 67.1 28 71.1 196 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 178 9 53 46 9.1 35.1 9.2 95 137 82.1 33.1 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.1 3.1 3.2 3.3 62 65 135 67.2 176.1 152 138 21.1 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 143 53.2 98.1 53.3 116.2 47.1 122 65.1 71.2 142.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[71]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0007757321 0.8634593724 0.7867148860
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.31319800 0.02262863 0.50427175
#> grade_iii, Cure model
#> 0.84739905
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 164 23.60 1 76 0 1
#> 149 8.37 1 33 1 0
#> 37 12.52 1 57 1 0
#> 177 12.53 1 75 0 0
#> 106 16.67 1 49 1 0
#> 100 16.07 1 60 0 0
#> 175 21.91 1 43 0 0
#> 29 15.45 1 68 1 0
#> 32 20.90 1 37 1 0
#> 101 9.97 1 10 0 1
#> 130 16.47 1 53 0 1
#> 76 19.22 1 54 0 1
#> 199 19.81 1 NA 0 1
#> 77 7.27 1 67 0 1
#> 49 12.19 1 48 1 0
#> 189 10.51 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 30 17.43 1 78 0 0
#> 153 21.33 1 55 1 0
#> 114 13.68 1 NA 0 0
#> 37.1 12.52 1 57 1 0
#> 56 12.21 1 60 0 0
#> 50 10.02 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 133 14.65 1 57 0 0
#> 51 18.23 1 83 0 1
#> 69 23.23 1 25 0 1
#> 93 10.33 1 52 0 1
#> 36 21.19 1 48 0 1
#> 188 16.16 1 46 0 1
#> 113 22.86 1 34 0 0
#> 134 17.81 1 47 1 0
#> 15.1 22.68 1 48 0 0
#> 77.1 7.27 1 67 0 1
#> 52 10.42 1 52 0 1
#> 192 16.44 1 31 1 0
#> 6 15.64 1 39 0 0
#> 37.2 12.52 1 57 1 0
#> 157 15.10 1 47 0 0
#> 40 18.00 1 28 1 0
#> 130.1 16.47 1 53 0 1
#> 184 17.77 1 38 0 0
#> 60.1 13.15 1 38 1 0
#> 189.1 10.51 1 NA 1 0
#> 63 22.77 1 31 1 0
#> 123 13.00 1 44 1 0
#> 195 11.76 1 NA 1 0
#> 29.1 15.45 1 68 1 0
#> 145 10.07 1 65 1 0
#> 77.2 7.27 1 67 0 1
#> 51.1 18.23 1 83 0 1
#> 158 20.14 1 74 1 0
#> 159 10.55 1 50 0 1
#> 105 19.75 1 60 0 0
#> 145.1 10.07 1 65 1 0
#> 89 11.44 1 NA 0 0
#> 124 9.73 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 139 21.49 1 63 1 0
#> 177.1 12.53 1 75 0 0
#> 168 23.72 1 70 0 0
#> 59 10.16 1 NA 1 0
#> 51.2 18.23 1 83 0 1
#> 52.1 10.42 1 52 0 1
#> 159.1 10.55 1 50 0 1
#> 66 22.13 1 53 0 0
#> 45 17.42 1 54 0 1
#> 99 21.19 1 38 0 1
#> 23 16.92 1 61 0 0
#> 70 7.38 1 30 1 0
#> 133.1 14.65 1 57 0 0
#> 49.1 12.19 1 48 1 0
#> 168.1 23.72 1 70 0 0
#> 42 12.43 1 49 0 1
#> 136 21.83 1 43 0 1
#> 114.1 13.68 1 NA 0 0
#> 4 17.64 1 NA 0 1
#> 24 23.89 1 38 0 0
#> 58 19.34 1 39 0 0
#> 66.1 22.13 1 53 0 0
#> 70.1 7.38 1 30 1 0
#> 168.2 23.72 1 70 0 0
#> 188.1 16.16 1 46 0 1
#> 113.1 22.86 1 34 0 0
#> 8 18.43 1 32 0 0
#> 169 22.41 1 46 0 0
#> 57 14.46 1 45 0 1
#> 58.1 19.34 1 39 0 0
#> 129 23.41 1 53 1 0
#> 123.1 13.00 1 44 1 0
#> 123.2 13.00 1 44 1 0
#> 16 8.71 1 71 0 1
#> 175.1 21.91 1 43 0 0
#> 117 17.46 1 26 0 1
#> 37.3 12.52 1 57 1 0
#> 88 18.37 1 47 0 0
#> 78 23.88 1 43 0 0
#> 61 10.12 1 36 0 1
#> 36.1 21.19 1 48 0 1
#> 15.2 22.68 1 48 0 0
#> 170 19.54 1 43 0 1
#> 14 12.89 1 21 0 0
#> 4.1 17.64 1 NA 0 1
#> 158.1 20.14 1 74 1 0
#> 63.1 22.77 1 31 1 0
#> 150 20.33 1 48 0 0
#> 79 16.23 1 54 1 0
#> 52.2 10.42 1 52 0 1
#> 164.1 23.60 1 76 0 1
#> 128 20.35 1 35 0 1
#> 40.1 18.00 1 28 1 0
#> 91 5.33 1 61 0 1
#> 80 24.00 0 41 0 0
#> 198 24.00 0 66 0 1
#> 11 24.00 0 42 0 1
#> 109 24.00 0 48 0 0
#> 109.1 24.00 0 48 0 0
#> 21 24.00 0 47 0 0
#> 73 24.00 0 NA 0 1
#> 109.2 24.00 0 48 0 0
#> 191 24.00 0 60 0 1
#> 141 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 12 24.00 0 63 0 0
#> 95 24.00 0 68 0 1
#> 152 24.00 0 36 0 1
#> 33 24.00 0 53 0 0
#> 144 24.00 0 28 0 1
#> 172 24.00 0 41 0 0
#> 115.1 24.00 0 NA 1 0
#> 200 24.00 0 64 0 0
#> 102 24.00 0 49 0 0
#> 103 24.00 0 56 1 0
#> 34 24.00 0 36 0 0
#> 87 24.00 0 27 0 0
#> 112 24.00 0 61 0 0
#> 102.1 24.00 0 49 0 0
#> 161 24.00 0 45 0 0
#> 118 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 115.2 24.00 0 NA 1 0
#> 191.1 24.00 0 60 0 1
#> 94 24.00 0 51 0 1
#> 126 24.00 0 48 0 0
#> 165 24.00 0 47 0 0
#> 1 24.00 0 23 1 0
#> 44 24.00 0 56 0 0
#> 34.1 24.00 0 36 0 0
#> 46 24.00 0 71 0 0
#> 9 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 160.1 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 115.3 24.00 0 NA 1 0
#> 44.1 24.00 0 56 0 0
#> 95.1 24.00 0 68 0 1
#> 7 24.00 0 37 1 0
#> 46.1 24.00 0 71 0 0
#> 161.1 24.00 0 45 0 0
#> 132 24.00 0 55 0 0
#> 172.1 24.00 0 41 0 0
#> 98 24.00 0 34 1 0
#> 67 24.00 0 25 0 0
#> 178 24.00 0 52 1 0
#> 185 24.00 0 44 1 0
#> 132.1 24.00 0 55 0 0
#> 47 24.00 0 38 0 1
#> 35 24.00 0 51 0 0
#> 47.1 24.00 0 38 0 1
#> 82 24.00 0 34 0 0
#> 174 24.00 0 49 1 0
#> 95.2 24.00 0 68 0 1
#> 132.2 24.00 0 55 0 0
#> 186 24.00 0 45 1 0
#> 137 24.00 0 45 1 0
#> 138.1 24.00 0 44 1 0
#> 46.2 24.00 0 71 0 0
#> 104 24.00 0 50 1 0
#> 144.1 24.00 0 28 0 1
#> 118.1 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 72 24.00 0 40 0 1
#> 7.1 24.00 0 37 1 0
#> 193 24.00 0 45 0 1
#> 118.2 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 80.1 24.00 0 41 0 0
#> 82.1 24.00 0 34 0 0
#> 109.3 24.00 0 48 0 0
#> 48.1 24.00 0 31 1 0
#> 102.2 24.00 0 49 0 0
#> 186.1 24.00 0 45 1 0
#> 173 24.00 0 19 0 1
#> 131 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 122 24.00 0 66 0 0
#> 3 24.00 0 31 1 0
#> 144.2 24.00 0 28 0 1
#> 141.1 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.31 NA NA NA
#> 2 age, Cure model 0.0226 NA NA NA
#> 3 grade_ii, Cure model 0.504 NA NA NA
#> 4 grade_iii, Cure model 0.847 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000776 NA NA NA
#> 2 grade_ii, Survival model 0.863 NA NA NA
#> 3 grade_iii, Survival model 0.787 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.31320 0.02263 0.50427 0.84740
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 252.1
#> Residual Deviance: 242.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.31319800 0.02262863 0.50427175 0.84739905
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0007757321 0.8634593724 0.7867148860
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.14953173 0.96042192 0.84230325 0.82872028 0.67524802 0.72917522
#> [7] 0.35722167 0.74410387 0.45418490 0.94865606 0.68331496 0.54419486
#> [13] 0.97765686 0.88118759 0.27783481 0.65056570 0.40975261 0.84230325
#> [19] 0.87469228 0.78760944 0.76588299 0.57276737 0.20459402 0.92467103
#> [25] 0.42187746 0.71433209 0.22050765 0.61676305 0.27783481 0.97765686
#> [31] 0.90639597 0.69894721 0.73663842 0.84230325 0.75859831 0.59949339
#> [37] 0.68331496 0.62530426 0.78760944 0.25130481 0.80163913 0.74410387
#> [43] 0.93680111 0.97765686 0.57276737 0.48573629 0.89389064 0.50534380
#> [49] 0.93680111 0.63384887 0.39715349 0.82872028 0.07982520 0.57276737
#> [55] 0.90639597 0.89389064 0.33047945 0.65886766 0.42187746 0.66705552
#> [61] 0.96623874 0.76588299 0.88118759 0.07982520 0.86819917 0.38403064
#> [67] 0.01701279 0.52495326 0.33047945 0.96623874 0.07982520 0.71433209
#> [73] 0.22050765 0.55371443 0.31687220 0.78039495 0.52495326 0.18711292
#> [79] 0.80163913 0.80163913 0.95455854 0.35722167 0.64226995 0.84230325
#> [85] 0.56323801 0.04764998 0.93075851 0.42187746 0.27783481 0.51525338
#> [91] 0.82190708 0.48573629 0.25130481 0.47530450 0.70669299 0.90639597
#> [97] 0.14953173 0.46488107 0.59949339 0.99441635 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 164 149 37 177 106 100 175 29 32 101 130 76 77
#> 23.60 8.37 12.52 12.53 16.67 16.07 21.91 15.45 20.90 9.97 16.47 19.22 7.27
#> 49 15 30 153 37.1 56 60 133 51 69 93 36 188
#> 12.19 22.68 17.43 21.33 12.52 12.21 13.15 14.65 18.23 23.23 10.33 21.19 16.16
#> 113 134 15.1 77.1 52 192 6 37.2 157 40 130.1 184 60.1
#> 22.86 17.81 22.68 7.27 10.42 16.44 15.64 12.52 15.10 18.00 16.47 17.77 13.15
#> 63 123 29.1 145 77.2 51.1 158 159 105 145.1 110 139 177.1
#> 22.77 13.00 15.45 10.07 7.27 18.23 20.14 10.55 19.75 10.07 17.56 21.49 12.53
#> 168 51.2 52.1 159.1 66 45 99 23 70 133.1 49.1 168.1 42
#> 23.72 18.23 10.42 10.55 22.13 17.42 21.19 16.92 7.38 14.65 12.19 23.72 12.43
#> 136 24 58 66.1 70.1 168.2 188.1 113.1 8 169 57 58.1 129
#> 21.83 23.89 19.34 22.13 7.38 23.72 16.16 22.86 18.43 22.41 14.46 19.34 23.41
#> 123.1 123.2 16 175.1 117 37.3 88 78 61 36.1 15.2 170 14
#> 13.00 13.00 8.71 21.91 17.46 12.52 18.37 23.88 10.12 21.19 22.68 19.54 12.89
#> 158.1 63.1 150 79 52.2 164.1 128 40.1 91 80 198 11 109
#> 20.14 22.77 20.33 16.23 10.42 23.60 20.35 18.00 5.33 24.00 24.00 24.00 24.00
#> 109.1 21 109.2 191 141 12 95 152 33 144 172 200 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 34 87 112 102.1 161 118 160 191.1 94 126 165 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 34.1 46 9 71 160.1 138 44.1 95.1 7 46.1 161.1 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 98 67 178 185 132.1 47 35 47.1 82 174 95.2 132.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 137 138.1 46.2 104 144.1 118.1 148 72 7.1 193 118.2 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 80.1 82.1 109.3 48.1 102.2 186.1 173 131 62 122 3 144.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.1
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[72]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01690924 0.46226273 0.08640281
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.9313951390 0.0009467373 1.0319353959
#> grade_iii, Cure model
#> 1.8521750877
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 199 19.81 1 NA 0 1
#> 59 10.16 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 68 20.62 1 44 0 0
#> 70 7.38 1 30 1 0
#> 117 17.46 1 26 0 1
#> 130 16.47 1 53 0 1
#> 159 10.55 1 50 0 1
#> 4 17.64 1 NA 0 1
#> 13 14.34 1 54 0 1
#> 111 17.45 1 47 0 1
#> 4.1 17.64 1 NA 0 1
#> 140 12.68 1 59 1 0
#> 140.1 12.68 1 59 1 0
#> 81 14.06 1 34 0 0
#> 42 12.43 1 49 0 1
#> 180 14.82 1 37 0 0
#> 86 23.81 1 58 0 1
#> 57 14.46 1 45 0 1
#> 39 15.59 1 37 0 1
#> 43 12.10 1 61 0 1
#> 4.2 17.64 1 NA 0 1
#> 155 13.08 1 26 0 0
#> 153 21.33 1 55 1 0
#> 123 13.00 1 44 1 0
#> 140.2 12.68 1 59 1 0
#> 128 20.35 1 35 0 1
#> 86.1 23.81 1 58 0 1
#> 136 21.83 1 43 0 1
#> 91 5.33 1 61 0 1
#> 77 7.27 1 67 0 1
#> 36 21.19 1 48 0 1
#> 50 10.02 1 NA 1 0
#> 130.1 16.47 1 53 0 1
#> 52 10.42 1 52 0 1
#> 29 15.45 1 68 1 0
#> 16 8.71 1 71 0 1
#> 59.1 10.16 1 NA 1 0
#> 187 9.92 1 39 1 0
#> 32 20.90 1 37 1 0
#> 123.1 13.00 1 44 1 0
#> 190 20.81 1 42 1 0
#> 10 10.53 1 34 0 0
#> 167 15.55 1 56 1 0
#> 29.1 15.45 1 68 1 0
#> 168 23.72 1 70 0 0
#> 86.2 23.81 1 58 0 1
#> 52.1 10.42 1 52 0 1
#> 49 12.19 1 48 1 0
#> 86.3 23.81 1 58 0 1
#> 129 23.41 1 53 1 0
#> 177 12.53 1 75 0 0
#> 61 10.12 1 36 0 1
#> 91.1 5.33 1 61 0 1
#> 170 19.54 1 43 0 1
#> 153.1 21.33 1 55 1 0
#> 190.1 20.81 1 42 1 0
#> 6 15.64 1 39 0 0
#> 69 23.23 1 25 0 1
#> 86.4 23.81 1 58 0 1
#> 167.1 15.55 1 56 1 0
#> 199.1 19.81 1 NA 0 1
#> 129.1 23.41 1 53 1 0
#> 181 16.46 1 45 0 1
#> 159.1 10.55 1 50 0 1
#> 86.5 23.81 1 58 0 1
#> 14 12.89 1 21 0 0
#> 93 10.33 1 52 0 1
#> 145 10.07 1 65 1 0
#> 164 23.60 1 76 0 1
#> 41 18.02 1 40 1 0
#> 24 23.89 1 38 0 0
#> 8 18.43 1 32 0 0
#> 140.3 12.68 1 59 1 0
#> 32.1 20.90 1 37 1 0
#> 97 19.14 1 65 0 1
#> 189 10.51 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 139 21.49 1 63 1 0
#> 36.1 21.19 1 48 0 1
#> 61.1 10.12 1 36 0 1
#> 111.1 17.45 1 47 0 1
#> 167.2 15.55 1 56 1 0
#> 97.1 19.14 1 65 0 1
#> 127 3.53 1 62 0 1
#> 125 15.65 1 67 1 0
#> 85 16.44 1 36 0 0
#> 111.2 17.45 1 47 0 1
#> 101 9.97 1 10 0 1
#> 25 6.32 1 34 1 0
#> 194 22.40 1 38 0 1
#> 166 19.98 1 48 0 0
#> 106 16.67 1 49 1 0
#> 105 19.75 1 60 0 0
#> 97.2 19.14 1 65 0 1
#> 183 9.24 1 67 1 0
#> 42.1 12.43 1 49 0 1
#> 154 12.63 1 20 1 0
#> 181.1 16.46 1 45 0 1
#> 36.2 21.19 1 48 0 1
#> 50.1 10.02 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 40 18.00 1 28 1 0
#> 90 20.94 1 50 0 1
#> 187.1 9.92 1 39 1 0
#> 101.1 9.97 1 10 0 1
#> 170.1 19.54 1 43 0 1
#> 181.2 16.46 1 45 0 1
#> 114 13.68 1 NA 0 0
#> 40.1 18.00 1 28 1 0
#> 154.1 12.63 1 20 1 0
#> 164.1 23.60 1 76 0 1
#> 141 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 12 24.00 0 63 0 0
#> 132 24.00 0 55 0 0
#> 174 24.00 0 49 1 0
#> 121 24.00 0 57 1 0
#> 87 24.00 0 27 0 0
#> 138 24.00 0 44 1 0
#> 87.1 24.00 0 27 0 0
#> 137 24.00 0 45 1 0
#> 120 24.00 0 68 0 1
#> 137.1 24.00 0 45 1 0
#> 62 24.00 0 71 0 0
#> 120.1 24.00 0 68 0 1
#> 9 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 72 24.00 0 40 0 1
#> 193 24.00 0 45 0 1
#> 165 24.00 0 47 0 0
#> 74 24.00 0 43 0 1
#> 147 24.00 0 76 1 0
#> 138.1 24.00 0 44 1 0
#> 112.1 24.00 0 61 0 0
#> 3 24.00 0 31 1 0
#> 138.2 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 35 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 141.1 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 115 24.00 0 NA 1 0
#> 75 24.00 0 21 1 0
#> 135 24.00 0 58 1 0
#> 163 24.00 0 66 0 0
#> 163.1 24.00 0 66 0 0
#> 64.1 24.00 0 43 0 0
#> 137.2 24.00 0 45 1 0
#> 83 24.00 0 6 0 0
#> 120.2 24.00 0 68 0 1
#> 53 24.00 0 32 0 1
#> 162 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 200 24.00 0 64 0 0
#> 178 24.00 0 52 1 0
#> 82 24.00 0 34 0 0
#> 119 24.00 0 17 0 0
#> 34 24.00 0 36 0 0
#> 200.1 24.00 0 64 0 0
#> 161 24.00 0 45 0 0
#> 143 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 191 24.00 0 60 0 1
#> 21 24.00 0 47 0 0
#> 71 24.00 0 51 0 0
#> 156.1 24.00 0 50 1 0
#> 31 24.00 0 36 0 1
#> 73.1 24.00 0 NA 0 1
#> 21.1 24.00 0 47 0 0
#> 72.1 24.00 0 40 0 1
#> 163.2 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 44 24.00 0 56 0 0
#> 120.3 24.00 0 68 0 1
#> 65 24.00 0 57 1 0
#> 122 24.00 0 66 0 0
#> 44.1 24.00 0 56 0 0
#> 112.2 24.00 0 61 0 0
#> 22 24.00 0 52 1 0
#> 198 24.00 0 66 0 1
#> 47 24.00 0 38 0 1
#> 28 24.00 0 67 1 0
#> 38 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 152 24.00 0 36 0 1
#> 17 24.00 0 38 0 1
#> 103 24.00 0 56 1 0
#> 196.1 24.00 0 19 0 0
#> 28.1 24.00 0 67 1 0
#> 178.1 24.00 0 52 1 0
#> 174.1 24.00 0 49 1 0
#> 71.1 24.00 0 51 0 0
#> 162.1 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 160.1 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 193.1 24.00 0 45 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.931 NA NA NA
#> 2 age, Cure model 0.000947 NA NA NA
#> 3 grade_ii, Cure model 1.03 NA NA NA
#> 4 grade_iii, Cure model 1.85 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0169 NA NA NA
#> 2 grade_ii, Survival model 0.462 NA NA NA
#> 3 grade_iii, Survival model 0.0864 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.9313951 0.0009467 1.0319354 1.8521751
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.5
#> Residual Deviance: 234.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.9313951390 0.0009467373 1.0319353959 1.8521750877
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01690924 0.46226273 0.08640281
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0997096885 0.0870662508 0.8996550634 0.1930209581 0.2380817622
#> [6] 0.6510678482 0.4243817804 0.2017804950 0.5012760745 0.5012760745
#> [11] 0.4369347624 0.5944980172 0.3998656460 0.0007645327 0.4120342562
#> [16] 0.3198553693 0.6366499882 0.4496474548 0.0347903975 0.4624893195
#> [21] 0.5012760745 0.0933029667 0.0007645327 0.0264155834 0.9492182622
#> [26] 0.9160374246 0.0436688458 0.2380817622 0.6951643723 0.3644591489
#> [31] 0.8669442553 0.8191294440 0.0642351234 0.4624893195 0.0754598452
#> [36] 0.6802645693 0.3309694771 0.3644591489 0.0057284912 0.0007645327
#> [41] 0.6951643723 0.6224290196 0.0007645327 0.0129897255 0.5807081329
#> [46] 0.7407738529 0.9492182622 0.1203831730 0.0347903975 0.0754598452
#> [51] 0.3088999503 0.0191045253 0.0007645327 0.3309694771 0.0129897255
#> [56] 0.2574337161 0.6510678482 0.0007645327 0.4881619348 0.7253454083
#> [61] 0.7718303763 0.0077665803 0.1674702448 0.0001141987 0.1589034626
#> [66] 0.5012760745 0.0642351234 0.1350714132 0.8832858303 0.0304725827
#> [71] 0.0436688458 0.7407738529 0.2017804950 0.3309694771 0.1350714132
#> [76] 0.9828532502 0.2981290085 0.2875449320 0.2017804950 0.7876697180
#> [81] 0.9326121187 0.0226339090 0.1063492901 0.2286362823 0.1132276647
#> [86] 0.1350714132 0.8508070339 0.5944980172 0.5539077122 0.2574337161
#> [91] 0.0436688458 0.3878668724 0.1761224102 0.0585139933 0.8191294440
#> [96] 0.7876697180 0.1203831730 0.2574337161 0.1761224102 0.5539077122
#> [101] 0.0077665803 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000
#>
#> $Time
#> 158 68 70 117 130 159 13 111 140 140.1 81 42 180
#> 20.14 20.62 7.38 17.46 16.47 10.55 14.34 17.45 12.68 12.68 14.06 12.43 14.82
#> 86 57 39 43 155 153 123 140.2 128 86.1 136 91 77
#> 23.81 14.46 15.59 12.10 13.08 21.33 13.00 12.68 20.35 23.81 21.83 5.33 7.27
#> 36 130.1 52 29 16 187 32 123.1 190 10 167 29.1 168
#> 21.19 16.47 10.42 15.45 8.71 9.92 20.90 13.00 20.81 10.53 15.55 15.45 23.72
#> 86.2 52.1 49 86.3 129 177 61 91.1 170 153.1 190.1 6 69
#> 23.81 10.42 12.19 23.81 23.41 12.53 10.12 5.33 19.54 21.33 20.81 15.64 23.23
#> 86.4 167.1 129.1 181 159.1 86.5 14 93 145 164 41 24 8
#> 23.81 15.55 23.41 16.46 10.55 23.81 12.89 10.33 10.07 23.60 18.02 23.89 18.43
#> 140.3 32.1 97 149 139 36.1 61.1 111.1 167.2 97.1 127 125 85
#> 12.68 20.90 19.14 8.37 21.49 21.19 10.12 17.45 15.55 19.14 3.53 15.65 16.44
#> 111.2 101 25 194 166 106 105 97.2 183 42.1 154 181.1 36.2
#> 17.45 9.97 6.32 22.40 19.98 16.67 19.75 19.14 9.24 12.43 12.63 16.46 21.19
#> 18 40 90 187.1 101.1 170.1 181.2 40.1 154.1 164.1 141 112 12
#> 15.21 18.00 20.94 9.92 9.97 19.54 16.46 18.00 12.63 23.60 24.00 24.00 24.00
#> 132 174 121 87 138 87.1 137 120 137.1 62 120.1 9 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 193 165 74 147 138.1 112.1 3 138.2 7 35 141.1 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 135 163 163.1 64.1 137.2 83 120.2 53 162 116 200 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 119 34 200.1 161 143 156 191 21 71 156.1 31 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 163.2 185 19 44 120.3 65 122 44.1 112.2 22 198 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 38 98 152 17 103 196.1 28.1 178.1 174.1 71.1 162.1 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.1 160.1 173 193.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[73]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009534539 0.403209162 0.328945634
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.285799384 0.003635672 0.043003112
#> grade_iii, Cure model
#> 0.897483421
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 59 10.16 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 170 19.54 1 43 0 1
#> 189 10.51 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 25 6.32 1 34 1 0
#> 13 14.34 1 54 0 1
#> 180 14.82 1 37 0 0
#> 168 23.72 1 70 0 0
#> 10 10.53 1 34 0 0
#> 181 16.46 1 45 0 1
#> 117 17.46 1 26 0 1
#> 29 15.45 1 68 1 0
#> 150 20.33 1 48 0 0
#> 36 21.19 1 48 0 1
#> 57 14.46 1 45 0 1
#> 68 20.62 1 44 0 0
#> 88 18.37 1 47 0 0
#> 99 21.19 1 38 0 1
#> 117.1 17.46 1 26 0 1
#> 192 16.44 1 31 1 0
#> 153 21.33 1 55 1 0
#> 134 17.81 1 47 1 0
#> 61 10.12 1 36 0 1
#> 157 15.10 1 47 0 0
#> 139 21.49 1 63 1 0
#> 97 19.14 1 65 0 1
#> 91 5.33 1 61 0 1
#> 23 16.92 1 61 0 0
#> 133 14.65 1 57 0 0
#> 40 18.00 1 28 1 0
#> 183 9.24 1 67 1 0
#> 45 17.42 1 54 0 1
#> 170.1 19.54 1 43 0 1
#> 60 13.15 1 38 1 0
#> 86 23.81 1 58 0 1
#> 194 22.40 1 38 0 1
#> 157.1 15.10 1 47 0 0
#> 170.2 19.54 1 43 0 1
#> 79 16.23 1 54 1 0
#> 179 18.63 1 42 0 0
#> 123 13.00 1 44 1 0
#> 157.2 15.10 1 47 0 0
#> 6 15.64 1 39 0 0
#> 39 15.59 1 37 0 1
#> 70 7.38 1 30 1 0
#> 58 19.34 1 39 0 0
#> 129 23.41 1 53 1 0
#> 149 8.37 1 33 1 0
#> 14 12.89 1 21 0 0
#> 155 13.08 1 26 0 0
#> 70.1 7.38 1 30 1 0
#> 36.1 21.19 1 48 0 1
#> 78 23.88 1 43 0 0
#> 169 22.41 1 46 0 0
#> 183.1 9.24 1 67 1 0
#> 61.1 10.12 1 36 0 1
#> 129.1 23.41 1 53 1 0
#> 114 13.68 1 NA 0 0
#> 78.1 23.88 1 43 0 0
#> 91.1 5.33 1 61 0 1
#> 181.1 16.46 1 45 0 1
#> 179.1 18.63 1 42 0 0
#> 77 7.27 1 67 0 1
#> 188 16.16 1 46 0 1
#> 86.1 23.81 1 58 0 1
#> 69 23.23 1 25 0 1
#> 149.1 8.37 1 33 1 0
#> 169.1 22.41 1 46 0 0
#> 114.1 13.68 1 NA 0 0
#> 145 10.07 1 65 1 0
#> 192.1 16.44 1 31 1 0
#> 129.2 23.41 1 53 1 0
#> 169.2 22.41 1 46 0 0
#> 55 19.34 1 69 0 1
#> 93 10.33 1 52 0 1
#> 89 11.44 1 NA 0 0
#> 61.2 10.12 1 36 0 1
#> 181.2 16.46 1 45 0 1
#> 36.2 21.19 1 48 0 1
#> 183.2 9.24 1 67 1 0
#> 59.1 10.16 1 NA 1 0
#> 101 9.97 1 10 0 1
#> 42 12.43 1 49 0 1
#> 90.1 20.94 1 50 0 1
#> 58.1 19.34 1 39 0 0
#> 181.3 16.46 1 45 0 1
#> 195 11.76 1 NA 1 0
#> 23.1 16.92 1 61 0 0
#> 37 12.52 1 57 1 0
#> 57.1 14.46 1 45 0 1
#> 189.1 10.51 1 NA 1 0
#> 171 16.57 1 41 0 1
#> 129.3 23.41 1 53 1 0
#> 52 10.42 1 52 0 1
#> 43 12.10 1 61 0 1
#> 16 8.71 1 71 0 1
#> 166 19.98 1 48 0 0
#> 93.1 10.33 1 52 0 1
#> 14.1 12.89 1 21 0 0
#> 110 17.56 1 65 0 1
#> 23.2 16.92 1 61 0 0
#> 155.1 13.08 1 26 0 0
#> 145.1 10.07 1 65 1 0
#> 30 17.43 1 78 0 0
#> 16.1 8.71 1 71 0 1
#> 6.1 15.64 1 39 0 0
#> 145.2 10.07 1 65 1 0
#> 39.1 15.59 1 37 0 1
#> 153.1 21.33 1 55 1 0
#> 40.1 18.00 1 28 1 0
#> 171.1 16.57 1 41 0 1
#> 172 24.00 0 41 0 0
#> 103 24.00 0 56 1 0
#> 9 24.00 0 31 1 0
#> 103.1 24.00 0 56 1 0
#> 193 24.00 0 45 0 1
#> 191 24.00 0 60 0 1
#> 172.1 24.00 0 41 0 0
#> 182 24.00 0 35 0 0
#> 196 24.00 0 19 0 0
#> 80 24.00 0 41 0 0
#> 112 24.00 0 61 0 0
#> 47 24.00 0 38 0 1
#> 64 24.00 0 43 0 0
#> 118 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 162 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 148 24.00 0 61 1 0
#> 198 24.00 0 66 0 1
#> 75 24.00 0 21 1 0
#> 182.1 24.00 0 35 0 0
#> 94 24.00 0 51 0 1
#> 47.1 24.00 0 38 0 1
#> 28 24.00 0 67 1 0
#> 191.1 24.00 0 60 0 1
#> 94.1 24.00 0 51 0 1
#> 17 24.00 0 38 0 1
#> 176 24.00 0 43 0 1
#> 47.2 24.00 0 38 0 1
#> 193.1 24.00 0 45 0 1
#> 163 24.00 0 66 0 0
#> 20 24.00 0 46 1 0
#> 27 24.00 0 63 1 0
#> 162.1 24.00 0 51 0 0
#> 9.1 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 162.2 24.00 0 51 0 0
#> 28.1 24.00 0 67 1 0
#> 27.1 24.00 0 63 1 0
#> 84 24.00 0 39 0 1
#> 115 24.00 0 NA 1 0
#> 115.1 24.00 0 NA 1 0
#> 185 24.00 0 44 1 0
#> 191.2 24.00 0 60 0 1
#> 121 24.00 0 57 1 0
#> 102 24.00 0 49 0 0
#> 7 24.00 0 37 1 0
#> 95 24.00 0 68 0 1
#> 53 24.00 0 32 0 1
#> 38 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 65 24.00 0 57 1 0
#> 200 24.00 0 64 0 0
#> 72 24.00 0 40 0 1
#> 46 24.00 0 71 0 0
#> 109.1 24.00 0 48 0 0
#> 31 24.00 0 36 0 1
#> 2 24.00 0 9 0 0
#> 120 24.00 0 68 0 1
#> 75.1 24.00 0 21 1 0
#> 62 24.00 0 71 0 0
#> 22.1 24.00 0 52 1 0
#> 9.2 24.00 0 31 1 0
#> 112.1 24.00 0 61 0 0
#> 12 24.00 0 63 0 0
#> 83 24.00 0 6 0 0
#> 80.1 24.00 0 41 0 0
#> 196.1 24.00 0 19 0 0
#> 44 24.00 0 56 0 0
#> 20.1 24.00 0 46 1 0
#> 151 24.00 0 42 0 0
#> 34 24.00 0 36 0 0
#> 87 24.00 0 27 0 0
#> 7.1 24.00 0 37 1 0
#> 135 24.00 0 58 1 0
#> 95.1 24.00 0 68 0 1
#> 22.2 24.00 0 52 1 0
#> 131 24.00 0 66 0 0
#> 141 24.00 0 44 1 0
#> 20.2 24.00 0 46 1 0
#> 87.1 24.00 0 27 0 0
#> 67 24.00 0 25 0 0
#> 178 24.00 0 52 1 0
#> 196.2 24.00 0 19 0 0
#> 7.2 24.00 0 37 1 0
#> 115.2 24.00 0 NA 1 0
#> 53.1 24.00 0 32 0 1
#> 33 24.00 0 53 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.286 NA NA NA
#> 2 age, Cure model 0.00364 NA NA NA
#> 3 grade_ii, Cure model 0.0430 NA NA NA
#> 4 grade_iii, Cure model 0.897 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00953 NA NA NA
#> 2 grade_ii, Survival model 0.403 NA NA NA
#> 3 grade_iii, Survival model 0.329 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.285799 0.003636 0.043003 0.897483
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.1
#> Residual Deviance: 252 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.285799384 0.003635672 0.043003112 0.897483421
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009534539 0.403209162 0.328945634
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.590982351 0.190354938 0.147715907 0.966034883 0.623110468 0.569560983
#> [7] 0.023651533 0.731925336 0.406850626 0.318653233 0.527920384 0.172719592
#> [13] 0.117136153 0.601731670 0.164140088 0.270889393 0.117136153 0.318653233
#> [19] 0.446387700 0.101160539 0.299406472 0.776242043 0.538319815 0.092986103
#> [25] 0.242780683 0.977361513 0.357132936 0.580230219 0.280568347 0.853682616
#> [31] 0.347336948 0.190354938 0.633924916 0.011939686 0.084938803 0.538319815
#> [37] 0.190354938 0.466511044 0.252115234 0.666321678 0.538319815 0.486925907
#> [43] 0.507413341 0.932227521 0.216088898 0.031633587 0.909690218 0.677208452
#> [49] 0.644731673 0.932227521 0.117136153 0.002646062 0.063074618 0.853682616
#> [55] 0.776242043 0.031633587 0.002646062 0.977361513 0.406850626 0.252115234
#> [61] 0.954697323 0.476707123 0.011939686 0.055787481 0.909690218 0.063074618
#> [67] 0.809232859 0.446387700 0.031633587 0.063074618 0.216088898 0.754102952
#> [73] 0.776242043 0.406850626 0.117136153 0.853682616 0.842487784 0.709903141
#> [79] 0.147715907 0.216088898 0.406850626 0.357132936 0.698932756 0.601731670
#> [85] 0.386769154 0.031633587 0.743001427 0.720895462 0.887101118 0.181458568
#> [91] 0.754102952 0.677208452 0.308992030 0.357132936 0.644731673 0.809232859
#> [97] 0.337587625 0.887101118 0.486925907 0.809232859 0.507413341 0.101160539
#> [103] 0.280568347 0.386769154 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 96 170 90 25 13 180 168 10 181 117 29 150 36
#> 14.54 19.54 20.94 6.32 14.34 14.82 23.72 10.53 16.46 17.46 15.45 20.33 21.19
#> 57 68 88 99 117.1 192 153 134 61 157 139 97 91
#> 14.46 20.62 18.37 21.19 17.46 16.44 21.33 17.81 10.12 15.10 21.49 19.14 5.33
#> 23 133 40 183 45 170.1 60 86 194 157.1 170.2 79 179
#> 16.92 14.65 18.00 9.24 17.42 19.54 13.15 23.81 22.40 15.10 19.54 16.23 18.63
#> 123 157.2 6 39 70 58 129 149 14 155 70.1 36.1 78
#> 13.00 15.10 15.64 15.59 7.38 19.34 23.41 8.37 12.89 13.08 7.38 21.19 23.88
#> 169 183.1 61.1 129.1 78.1 91.1 181.1 179.1 77 188 86.1 69 149.1
#> 22.41 9.24 10.12 23.41 23.88 5.33 16.46 18.63 7.27 16.16 23.81 23.23 8.37
#> 169.1 145 192.1 129.2 169.2 55 93 61.2 181.2 36.2 183.2 101 42
#> 22.41 10.07 16.44 23.41 22.41 19.34 10.33 10.12 16.46 21.19 9.24 9.97 12.43
#> 90.1 58.1 181.3 23.1 37 57.1 171 129.3 52 43 16 166 93.1
#> 20.94 19.34 16.46 16.92 12.52 14.46 16.57 23.41 10.42 12.10 8.71 19.98 10.33
#> 14.1 110 23.2 155.1 145.1 30 16.1 6.1 145.2 39.1 153.1 40.1 171.1
#> 12.89 17.56 16.92 13.08 10.07 17.43 8.71 15.64 10.07 15.59 21.33 18.00 16.57
#> 172 103 9 103.1 193 191 172.1 182 196 80 112 47 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 161 162 137 148 198 75 182.1 94 47.1 28 191.1 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 176 47.2 193.1 163 20 27 162.1 9.1 22 162.2 28.1 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 185 191.2 121 102 7 95 53 38 109 65 200 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 109.1 31 2 120 75.1 62 22.1 9.2 112.1 12 83 80.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196.1 44 20.1 151 34 87 7.1 135 95.1 22.2 131 141 20.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1 67 178 196.2 7.2 53.1 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[74]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00512487 0.60039759 0.41916624
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.73768110 0.01691135 0.16650733
#> grade_iii, Cure model
#> 0.26437966
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 139 21.49 1 63 1 0
#> 56 12.21 1 60 0 0
#> 169 22.41 1 46 0 0
#> 63 22.77 1 31 1 0
#> 49 12.19 1 48 1 0
#> 111 17.45 1 47 0 1
#> 16 8.71 1 71 0 1
#> 13 14.34 1 54 0 1
#> 70 7.38 1 30 1 0
#> 39 15.59 1 37 0 1
#> 177 12.53 1 75 0 0
#> 39.1 15.59 1 37 0 1
#> 24 23.89 1 38 0 0
#> 41 18.02 1 40 1 0
#> 66 22.13 1 53 0 0
#> 100 16.07 1 60 0 0
#> 175 21.91 1 43 0 0
#> 111.1 17.45 1 47 0 1
#> 107 11.18 1 54 1 0
#> 101 9.97 1 10 0 1
#> 180 14.82 1 37 0 0
#> 32 20.90 1 37 1 0
#> 113 22.86 1 34 0 0
#> 90 20.94 1 50 0 1
#> 29 15.45 1 68 1 0
#> 30 17.43 1 78 0 0
#> 129 23.41 1 53 1 0
#> 32.1 20.90 1 37 1 0
#> 76 19.22 1 54 0 1
#> 85 16.44 1 36 0 0
#> 164 23.60 1 76 0 1
#> 30.1 17.43 1 78 0 0
#> 114 13.68 1 NA 0 0
#> 51 18.23 1 83 0 1
#> 8 18.43 1 32 0 0
#> 5 16.43 1 51 0 1
#> 150 20.33 1 48 0 0
#> 128 20.35 1 35 0 1
#> 113.1 22.86 1 34 0 0
#> 157 15.10 1 47 0 0
#> 23 16.92 1 61 0 0
#> 125 15.65 1 67 1 0
#> 68 20.62 1 44 0 0
#> 154 12.63 1 20 1 0
#> 110 17.56 1 65 0 1
#> 136 21.83 1 43 0 1
#> 88 18.37 1 47 0 0
#> 153 21.33 1 55 1 0
#> 39.2 15.59 1 37 0 1
#> 29.1 15.45 1 68 1 0
#> 175.1 21.91 1 43 0 0
#> 63.1 22.77 1 31 1 0
#> 125.1 15.65 1 67 1 0
#> 25 6.32 1 34 1 0
#> 61 10.12 1 36 0 1
#> 99 21.19 1 38 0 1
#> 167 15.55 1 56 1 0
#> 111.2 17.45 1 47 0 1
#> 154.1 12.63 1 20 1 0
#> 168 23.72 1 70 0 0
#> 61.1 10.12 1 36 0 1
#> 91 5.33 1 61 0 1
#> 23.1 16.92 1 61 0 0
#> 134 17.81 1 47 1 0
#> 4 17.64 1 NA 0 1
#> 154.2 12.63 1 20 1 0
#> 153.1 21.33 1 55 1 0
#> 134.1 17.81 1 47 1 0
#> 192 16.44 1 31 1 0
#> 130 16.47 1 53 0 1
#> 164.1 23.60 1 76 0 1
#> 123 13.00 1 44 1 0
#> 124 9.73 1 NA 1 0
#> 107.1 11.18 1 54 1 0
#> 101.1 9.97 1 10 0 1
#> 40 18.00 1 28 1 0
#> 180.1 14.82 1 37 0 0
#> 52 10.42 1 52 0 1
#> 78 23.88 1 43 0 0
#> 55 19.34 1 69 0 1
#> 52.1 10.42 1 52 0 1
#> 181 16.46 1 45 0 1
#> 133 14.65 1 57 0 0
#> 97 19.14 1 65 0 1
#> 158 20.14 1 74 1 0
#> 93 10.33 1 52 0 1
#> 194 22.40 1 38 0 1
#> 86 23.81 1 58 0 1
#> 30.2 17.43 1 78 0 0
#> 86.1 23.81 1 58 0 1
#> 124.1 9.73 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 134.2 17.81 1 47 1 0
#> 68.1 20.62 1 44 0 0
#> 188 16.16 1 46 0 1
#> 56.1 12.21 1 60 0 0
#> 41.1 18.02 1 40 1 0
#> 175.2 21.91 1 43 0 0
#> 113.2 22.86 1 34 0 0
#> 29.2 15.45 1 68 1 0
#> 6 15.64 1 39 0 0
#> 45 17.42 1 54 0 1
#> 197 21.60 1 69 1 0
#> 150.1 20.33 1 48 0 0
#> 49.1 12.19 1 48 1 0
#> 30.3 17.43 1 78 0 0
#> 192.1 16.44 1 31 1 0
#> 140 12.68 1 59 1 0
#> 37 12.52 1 57 1 0
#> 25.1 6.32 1 34 1 0
#> 117 17.46 1 26 0 1
#> 49.2 12.19 1 48 1 0
#> 28 24.00 0 67 1 0
#> 119 24.00 0 17 0 0
#> 137 24.00 0 45 1 0
#> 118 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 74 24.00 0 43 0 1
#> 116 24.00 0 58 0 1
#> 75 24.00 0 21 1 0
#> 120.1 24.00 0 68 0 1
#> 143 24.00 0 51 0 0
#> 131 24.00 0 66 0 0
#> 1 24.00 0 23 1 0
#> 137.1 24.00 0 45 1 0
#> 131.1 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 176 24.00 0 43 0 1
#> 27 24.00 0 63 1 0
#> 119.1 24.00 0 17 0 0
#> 126 24.00 0 48 0 0
#> 98 24.00 0 34 1 0
#> 173 24.00 0 19 0 1
#> 152 24.00 0 36 0 1
#> 9 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 186 24.00 0 45 1 0
#> 21 24.00 0 47 0 0
#> 98.1 24.00 0 34 1 0
#> 65 24.00 0 57 1 0
#> 67 24.00 0 25 0 0
#> 98.2 24.00 0 34 1 0
#> 147 24.00 0 76 1 0
#> 135 24.00 0 58 1 0
#> 156 24.00 0 50 1 0
#> 118.1 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 33 24.00 0 53 0 0
#> 163 24.00 0 66 0 0
#> 173.1 24.00 0 19 0 1
#> 193.1 24.00 0 45 0 1
#> 104 24.00 0 50 1 0
#> 121 24.00 0 57 1 0
#> 103 24.00 0 56 1 0
#> 138 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 46 24.00 0 71 0 0
#> 67.1 24.00 0 25 0 0
#> 161 24.00 0 45 0 0
#> 64 24.00 0 43 0 0
#> 186.1 24.00 0 45 1 0
#> 142.1 24.00 0 53 0 0
#> 185 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 1.1 24.00 0 23 1 0
#> 161.1 24.00 0 45 0 0
#> 80 24.00 0 41 0 0
#> 84 24.00 0 39 0 1
#> 31 24.00 0 36 0 1
#> 196 24.00 0 19 0 0
#> 141 24.00 0 44 1 0
#> 21.1 24.00 0 47 0 0
#> 47 24.00 0 38 0 1
#> 74.1 24.00 0 43 0 1
#> 19 24.00 0 57 0 1
#> 116.1 24.00 0 58 0 1
#> 131.2 24.00 0 66 0 0
#> 84.1 24.00 0 39 0 1
#> 53 24.00 0 32 0 1
#> 98.3 24.00 0 34 1 0
#> 120.2 24.00 0 68 0 1
#> 17 24.00 0 38 0 1
#> 53.1 24.00 0 32 0 1
#> 186.2 24.00 0 45 1 0
#> 112 24.00 0 61 0 0
#> 178 24.00 0 52 1 0
#> 84.2 24.00 0 39 0 1
#> 47.1 24.00 0 38 0 1
#> 137.2 24.00 0 45 1 0
#> 17.1 24.00 0 38 0 1
#> 9.1 24.00 0 31 1 0
#> 152.1 24.00 0 36 0 1
#> 165 24.00 0 47 0 0
#> 131.3 24.00 0 66 0 0
#> 109 24.00 0 48 0 0
#> 94 24.00 0 51 0 1
#> 116.2 24.00 0 58 0 1
#> 64.1 24.00 0 43 0 0
#> 143.1 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.738 NA NA NA
#> 2 age, Cure model 0.0169 NA NA NA
#> 3 grade_ii, Cure model 0.167 NA NA NA
#> 4 grade_iii, Cure model 0.264 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00512 NA NA NA
#> 2 grade_ii, Survival model 0.600 NA NA NA
#> 3 grade_iii, Survival model 0.419 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.73768 0.01691 0.16651 0.26438
#>
#> Degrees of Freedom: 195 Total (i.e. Null); 192 Residual
#> Null Deviance: 269.7
#> Residual Deviance: 266.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.73768110 0.01691135 0.16650733 0.26437966
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00512487 0.60039759 0.41916624
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.230657909 0.844193960 0.147206304 0.127161177 0.861034640 0.486764233
#> [7] 0.959694526 0.767865442 0.967843803 0.672969984 0.818877490 0.672969984
#> [13] 0.004817737 0.414247762 0.168123644 0.637649412 0.178649866 0.486764233
#> [19] 0.885863506 0.943457368 0.741887820 0.280604488 0.095695809 0.270715322
#> [25] 0.707656250 0.512900497 0.084494202 0.280604488 0.366293738 0.593485530
#> [31] 0.062529113 0.512900497 0.404615813 0.385404781 0.619871911 0.327959434
#> [37] 0.318386109 0.095695809 0.733237734 0.557266849 0.646558344 0.299374823
#> [43] 0.793826544 0.468771283 0.209428188 0.394985292 0.241049371 0.672969984
#> [49] 0.707656250 0.178649866 0.127161177 0.646558344 0.975954626 0.927094985
#> [55] 0.260761867 0.698932807 0.486764233 0.793826544 0.050271690 0.927094985
#> [61] 0.991968037 0.557266849 0.442170518 0.793826544 0.241049371 0.442170518
#> [67] 0.593485530 0.575341552 0.062529113 0.776559493 0.885863506 0.943457368
#> [73] 0.432872750 0.741887820 0.902375925 0.016237208 0.356688929 0.902375925
#> [79] 0.584428150 0.759156298 0.375860167 0.347066584 0.918838665 0.157752037
#> [85] 0.030041776 0.512900497 0.030041776 0.835775884 0.442170518 0.299374823
#> [91] 0.628773309 0.844193960 0.414247762 0.178649866 0.095695809 0.707656250
#> [97] 0.664112683 0.548234329 0.220114621 0.327959434 0.861034640 0.512900497
#> [103] 0.593485530 0.785209497 0.827342265 0.975954626 0.477795788 0.861034640
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 139 56 169 63 49 111 16 13 70 39 177 39.1 24
#> 21.49 12.21 22.41 22.77 12.19 17.45 8.71 14.34 7.38 15.59 12.53 15.59 23.89
#> 41 66 100 175 111.1 107 101 180 32 113 90 29 30
#> 18.02 22.13 16.07 21.91 17.45 11.18 9.97 14.82 20.90 22.86 20.94 15.45 17.43
#> 129 32.1 76 85 164 30.1 51 8 5 150 128 113.1 157
#> 23.41 20.90 19.22 16.44 23.60 17.43 18.23 18.43 16.43 20.33 20.35 22.86 15.10
#> 23 125 68 154 110 136 88 153 39.2 29.1 175.1 63.1 125.1
#> 16.92 15.65 20.62 12.63 17.56 21.83 18.37 21.33 15.59 15.45 21.91 22.77 15.65
#> 25 61 99 167 111.2 154.1 168 61.1 91 23.1 134 154.2 153.1
#> 6.32 10.12 21.19 15.55 17.45 12.63 23.72 10.12 5.33 16.92 17.81 12.63 21.33
#> 134.1 192 130 164.1 123 107.1 101.1 40 180.1 52 78 55 52.1
#> 17.81 16.44 16.47 23.60 13.00 11.18 9.97 18.00 14.82 10.42 23.88 19.34 10.42
#> 181 133 97 158 93 194 86 30.2 86.1 42 134.2 68.1 188
#> 16.46 14.65 19.14 20.14 10.33 22.40 23.81 17.43 23.81 12.43 17.81 20.62 16.16
#> 56.1 41.1 175.2 113.2 29.2 6 45 197 150.1 49.1 30.3 192.1 140
#> 12.21 18.02 21.91 22.86 15.45 15.64 17.42 21.60 20.33 12.19 17.43 16.44 12.68
#> 37 25.1 117 49.2 28 119 137 118 122 120 74 116 75
#> 12.52 6.32 17.46 12.19 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 143 131 1 137.1 131.1 22 176 27 119.1 126 98 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 9 193 186 21 98.1 65 67 98.2 147 135 156 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 33 163 173.1 193.1 104 121 103 138 142 46 67.1 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 186.1 142.1 185 182 1.1 161.1 80 84 31 196 141 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 74.1 19 116.1 131.2 84.1 53 98.3 120.2 17 53.1 186.2 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 84.2 47.1 137.2 17.1 9.1 152.1 165 131.3 109 94 116.2 64.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143.1
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[75]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001948801 0.390769847 0.012946451
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.76544737 0.01482005 -0.12118452
#> grade_iii, Cure model
#> 1.39356443
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 134 17.81 1 47 1 0
#> 14 12.89 1 21 0 0
#> 60 13.15 1 38 1 0
#> 13 14.34 1 54 0 1
#> 194 22.40 1 38 0 1
#> 56 12.21 1 60 0 0
#> 167 15.55 1 56 1 0
#> 167.1 15.55 1 56 1 0
#> 157 15.10 1 47 0 0
#> 153 21.33 1 55 1 0
#> 70 7.38 1 30 1 0
#> 13.1 14.34 1 54 0 1
#> 129 23.41 1 53 1 0
#> 86 23.81 1 58 0 1
#> 69 23.23 1 25 0 1
#> 192 16.44 1 31 1 0
#> 153.1 21.33 1 55 1 0
#> 155 13.08 1 26 0 0
#> 30 17.43 1 78 0 0
#> 86.1 23.81 1 58 0 1
#> 97 19.14 1 65 0 1
#> 76 19.22 1 54 0 1
#> 36 21.19 1 48 0 1
#> 170 19.54 1 43 0 1
#> 55 19.34 1 69 0 1
#> 41 18.02 1 40 1 0
#> 24 23.89 1 38 0 0
#> 127 3.53 1 62 0 1
#> 154 12.63 1 20 1 0
#> 13.2 14.34 1 54 0 1
#> 79 16.23 1 54 1 0
#> 177 12.53 1 75 0 0
#> 86.2 23.81 1 58 0 1
#> 70.1 7.38 1 30 1 0
#> 26 15.77 1 49 0 1
#> 4 17.64 1 NA 0 1
#> 111 17.45 1 47 0 1
#> 114 13.68 1 NA 0 0
#> 100 16.07 1 60 0 0
#> 76.1 19.22 1 54 0 1
#> 139 21.49 1 63 1 0
#> 32 20.90 1 37 1 0
#> 14.1 12.89 1 21 0 0
#> 166 19.98 1 48 0 0
#> 179 18.63 1 42 0 0
#> 78 23.88 1 43 0 0
#> 42 12.43 1 49 0 1
#> 100.1 16.07 1 60 0 0
#> 117 17.46 1 26 0 1
#> 56.1 12.21 1 60 0 0
#> 195 11.76 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 77 7.27 1 67 0 1
#> 77.1 7.27 1 67 0 1
#> 100.2 16.07 1 60 0 0
#> 177.1 12.53 1 75 0 0
#> 85 16.44 1 36 0 0
#> 106 16.67 1 49 1 0
#> 78.1 23.88 1 43 0 0
#> 66 22.13 1 53 0 0
#> 134.1 17.81 1 47 1 0
#> 51 18.23 1 83 0 1
#> 133 14.65 1 57 0 0
#> 167.2 15.55 1 56 1 0
#> 159 10.55 1 50 0 1
#> 55.1 19.34 1 69 0 1
#> 183 9.24 1 67 1 0
#> 125 15.65 1 67 1 0
#> 106.1 16.67 1 49 1 0
#> 25 6.32 1 34 1 0
#> 167.3 15.55 1 56 1 0
#> 68 20.62 1 44 0 0
#> 55.2 19.34 1 69 0 1
#> 8 18.43 1 32 0 0
#> 13.3 14.34 1 54 0 1
#> 159.1 10.55 1 50 0 1
#> 14.2 12.89 1 21 0 0
#> 76.2 19.22 1 54 0 1
#> 92 22.92 1 47 0 1
#> 133.1 14.65 1 57 0 0
#> 101 9.97 1 10 0 1
#> 153.2 21.33 1 55 1 0
#> 188 16.16 1 46 0 1
#> 86.3 23.81 1 58 0 1
#> 113 22.86 1 34 0 0
#> 6 15.64 1 39 0 0
#> 60.1 13.15 1 38 1 0
#> 8.1 18.43 1 32 0 0
#> 197 21.60 1 69 1 0
#> 127.1 3.53 1 62 0 1
#> 140 12.68 1 59 1 0
#> 140.1 12.68 1 59 1 0
#> 96 14.54 1 33 0 1
#> 194.1 22.40 1 38 0 1
#> 97.1 19.14 1 65 0 1
#> 6.1 15.64 1 39 0 0
#> 110 17.56 1 65 0 1
#> 195.1 11.76 1 NA 1 0
#> 26.1 15.77 1 49 0 1
#> 86.4 23.81 1 58 0 1
#> 155.1 13.08 1 26 0 0
#> 89 11.44 1 NA 0 0
#> 52 10.42 1 52 0 1
#> 133.2 14.65 1 57 0 0
#> 14.3 12.89 1 21 0 0
#> 159.2 10.55 1 50 0 1
#> 42.1 12.43 1 49 0 1
#> 166.1 19.98 1 48 0 0
#> 113.1 22.86 1 34 0 0
#> 136 21.83 1 43 0 1
#> 140.2 12.68 1 59 1 0
#> 37 12.52 1 57 1 0
#> 182 24.00 0 35 0 0
#> 112 24.00 0 61 0 0
#> 75 24.00 0 21 1 0
#> 28 24.00 0 67 1 0
#> 94 24.00 0 51 0 1
#> 104 24.00 0 50 1 0
#> 9 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 20 24.00 0 46 1 0
#> 64 24.00 0 43 0 0
#> 200 24.00 0 64 0 0
#> 46 24.00 0 71 0 0
#> 142 24.00 0 53 0 0
#> 162 24.00 0 51 0 0
#> 3 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 54 24.00 0 53 1 0
#> 73 24.00 0 NA 0 1
#> 172.1 24.00 0 41 0 0
#> 80 24.00 0 41 0 0
#> 7 24.00 0 37 1 0
#> 67 24.00 0 25 0 0
#> 172.2 24.00 0 41 0 0
#> 172.3 24.00 0 41 0 0
#> 87 24.00 0 27 0 0
#> 174 24.00 0 49 1 0
#> 35 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 152 24.00 0 36 0 1
#> 148 24.00 0 61 1 0
#> 73.1 24.00 0 NA 0 1
#> 3.1 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 142.1 24.00 0 53 0 0
#> 112.1 24.00 0 61 0 0
#> 198 24.00 0 66 0 1
#> 7.1 24.00 0 37 1 0
#> 185 24.00 0 44 1 0
#> 47 24.00 0 38 0 1
#> 186 24.00 0 45 1 0
#> 186.1 24.00 0 45 1 0
#> 172.4 24.00 0 41 0 0
#> 27 24.00 0 63 1 0
#> 38.1 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 27.1 24.00 0 63 1 0
#> 53 24.00 0 32 0 1
#> 82 24.00 0 34 0 0
#> 44 24.00 0 56 0 0
#> 165.1 24.00 0 47 0 0
#> 191 24.00 0 60 0 1
#> 163 24.00 0 66 0 0
#> 64.1 24.00 0 43 0 0
#> 28.1 24.00 0 67 1 0
#> 3.2 24.00 0 31 1 0
#> 200.1 24.00 0 64 0 0
#> 75.1 24.00 0 21 1 0
#> 142.2 24.00 0 53 0 0
#> 200.2 24.00 0 64 0 0
#> 174.1 24.00 0 49 1 0
#> 121 24.00 0 57 1 0
#> 28.2 24.00 0 67 1 0
#> 172.5 24.00 0 41 0 0
#> 1 24.00 0 23 1 0
#> 178 24.00 0 52 1 0
#> 121.1 24.00 0 57 1 0
#> 103 24.00 0 56 1 0
#> 109 24.00 0 48 0 0
#> 165.2 24.00 0 47 0 0
#> 144 24.00 0 28 0 1
#> 163.1 24.00 0 66 0 0
#> 28.3 24.00 0 67 1 0
#> 174.2 24.00 0 49 1 0
#> 73.2 24.00 0 NA 0 1
#> 115 24.00 0 NA 1 0
#> 47.1 24.00 0 38 0 1
#> 193 24.00 0 45 0 1
#> 182.1 24.00 0 35 0 0
#> 152.1 24.00 0 36 0 1
#> 126 24.00 0 48 0 0
#> 185.1 24.00 0 44 1 0
#> 67.1 24.00 0 25 0 0
#> 71 24.00 0 51 0 0
#> 121.2 24.00 0 57 1 0
#> 83 24.00 0 6 0 0
#> 17 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.765 NA NA NA
#> 2 age, Cure model 0.0148 NA NA NA
#> 3 grade_ii, Cure model -0.121 NA NA NA
#> 4 grade_iii, Cure model 1.39 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00195 NA NA NA
#> 2 grade_ii, Survival model 0.391 NA NA NA
#> 3 grade_iii, Survival model 0.0129 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.76545 0.01482 -0.12118 1.39356
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262
#> Residual Deviance: 242.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.76544737 0.01482005 -0.12118452 1.39356443
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001948801 0.390769847 0.012946451
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.407518728 0.748223822 0.711831856 0.675586393 0.130448018 0.865167408
#> [7] 0.594188401 0.594188401 0.630002024 0.201052577 0.937333353 0.675586393
#> [13] 0.080976708 0.040790400 0.090931568 0.482988473 0.201052577 0.730016624
#> [19] 0.454792334 0.040790400 0.340313825 0.312331912 0.228301432 0.275108696
#> [25] 0.284570768 0.397880346 0.006746339 0.982108124 0.811158188 0.675586393
#> [31] 0.501517866 0.820181018 0.040790400 0.937333353 0.547705152 0.445269470
#> [37] 0.520119612 0.312331912 0.191061886 0.237802371 0.748223822 0.256552938
#> [43] 0.359347893 0.019803632 0.847198401 0.520119612 0.435761992 0.865167408
#> [49] 0.160305359 0.955216986 0.955216986 0.520119612 0.820181018 0.482988473
#> [55] 0.464343407 0.019803632 0.150078239 0.407518728 0.388155458 0.639164532
#> [61] 0.594188401 0.883177705 0.284570768 0.928280065 0.566303403 0.464343407
#> [67] 0.973137860 0.594188401 0.247163023 0.284570768 0.369014814 0.675586393
#> [73] 0.883177705 0.748223822 0.312331912 0.100925941 0.639164532 0.919200462
#> [79] 0.201052577 0.510812485 0.040790400 0.110996501 0.575634248 0.711831856
#> [85] 0.369014814 0.180908176 0.982108124 0.784264966 0.784264966 0.666381360
#> [91] 0.130448018 0.340313825 0.575634248 0.426262194 0.547705152 0.040790400
#> [97] 0.730016624 0.910121444 0.639164532 0.748223822 0.883177705 0.847198401
#> [103] 0.256552938 0.110996501 0.170585404 0.784264966 0.838180987 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 134 14 60 13 194 56 167 167.1 157 153 70 13.1 129
#> 17.81 12.89 13.15 14.34 22.40 12.21 15.55 15.55 15.10 21.33 7.38 14.34 23.41
#> 86 69 192 153.1 155 30 86.1 97 76 36 170 55 41
#> 23.81 23.23 16.44 21.33 13.08 17.43 23.81 19.14 19.22 21.19 19.54 19.34 18.02
#> 24 127 154 13.2 79 177 86.2 70.1 26 111 100 76.1 139
#> 23.89 3.53 12.63 14.34 16.23 12.53 23.81 7.38 15.77 17.45 16.07 19.22 21.49
#> 32 14.1 166 179 78 42 100.1 117 56.1 175 77 77.1 100.2
#> 20.90 12.89 19.98 18.63 23.88 12.43 16.07 17.46 12.21 21.91 7.27 7.27 16.07
#> 177.1 85 106 78.1 66 134.1 51 133 167.2 159 55.1 183 125
#> 12.53 16.44 16.67 23.88 22.13 17.81 18.23 14.65 15.55 10.55 19.34 9.24 15.65
#> 106.1 25 167.3 68 55.2 8 13.3 159.1 14.2 76.2 92 133.1 101
#> 16.67 6.32 15.55 20.62 19.34 18.43 14.34 10.55 12.89 19.22 22.92 14.65 9.97
#> 153.2 188 86.3 113 6 60.1 8.1 197 127.1 140 140.1 96 194.1
#> 21.33 16.16 23.81 22.86 15.64 13.15 18.43 21.60 3.53 12.68 12.68 14.54 22.40
#> 97.1 6.1 110 26.1 86.4 155.1 52 133.2 14.3 159.2 42.1 166.1 113.1
#> 19.14 15.64 17.56 15.77 23.81 13.08 10.42 14.65 12.89 10.55 12.43 19.98 22.86
#> 136 140.2 37 182 112 75 28 94 104 9 48 172 20
#> 21.83 12.68 12.52 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 200 46 142 162 3 98 54 172.1 80 7 67 172.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.3 87 174 35 165 152 148 3.1 38 118 142.1 112.1 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.1 185 47 186 186.1 172.4 27 38.1 161 27.1 53 82 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.1 191 163 64.1 28.1 3.2 200.1 75.1 142.2 200.2 174.1 121 28.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.5 1 178 121.1 103 109 165.2 144 163.1 28.3 174.2 47.1 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.1 152.1 126 185.1 67.1 71 121.2 83 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[76]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001652986 0.902151876 0.307543913
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.453956356 0.006959073 0.186371773
#> grade_iii, Cure model
#> 0.728953638
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 179 18.63 1 42 0 0
#> 99 21.19 1 38 0 1
#> 133 14.65 1 57 0 0
#> 108 18.29 1 39 0 1
#> 42 12.43 1 49 0 1
#> 6 15.64 1 39 0 0
#> 13 14.34 1 54 0 1
#> 155 13.08 1 26 0 0
#> 170 19.54 1 43 0 1
#> 97 19.14 1 65 0 1
#> 26 15.77 1 49 0 1
#> 107 11.18 1 54 1 0
#> 195 11.76 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 86 23.81 1 58 0 1
#> 168 23.72 1 70 0 0
#> 52 10.42 1 52 0 1
#> 189 10.51 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 157 15.10 1 47 0 0
#> 24 23.89 1 38 0 0
#> 5 16.43 1 51 0 1
#> 78 23.88 1 43 0 0
#> 78.1 23.88 1 43 0 0
#> 197 21.60 1 69 1 0
#> 189.1 10.51 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 30 17.43 1 78 0 0
#> 78.2 23.88 1 43 0 0
#> 158 20.14 1 74 1 0
#> 145 10.07 1 65 1 0
#> 157.1 15.10 1 47 0 0
#> 192 16.44 1 31 1 0
#> 175 21.91 1 43 0 0
#> 179.1 18.63 1 42 0 0
#> 76 19.22 1 54 0 1
#> 70 7.38 1 30 1 0
#> 188 16.16 1 46 0 1
#> 79 16.23 1 54 1 0
#> 18 15.21 1 49 1 0
#> 183 9.24 1 67 1 0
#> 52.1 10.42 1 52 0 1
#> 184 17.77 1 38 0 0
#> 171 16.57 1 41 0 1
#> 194 22.40 1 38 0 1
#> 25 6.32 1 34 1 0
#> 108.1 18.29 1 39 0 1
#> 133.1 14.65 1 57 0 0
#> 195.1 11.76 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 5.1 16.43 1 51 0 1
#> 15 22.68 1 48 0 0
#> 158.1 20.14 1 74 1 0
#> 107.1 11.18 1 54 1 0
#> 105 19.75 1 60 0 0
#> 145.1 10.07 1 65 1 0
#> 85 16.44 1 36 0 0
#> 130 16.47 1 53 0 1
#> 114 13.68 1 NA 0 0
#> 149 8.37 1 33 1 0
#> 136 21.83 1 43 0 1
#> 157.2 15.10 1 47 0 0
#> 183.1 9.24 1 67 1 0
#> 10 10.53 1 34 0 0
#> 180 14.82 1 37 0 0
#> 57.1 14.46 1 45 0 1
#> 140 12.68 1 59 1 0
#> 114.1 13.68 1 NA 0 0
#> 106 16.67 1 49 1 0
#> 169 22.41 1 46 0 0
#> 188.1 16.16 1 46 0 1
#> 159 10.55 1 50 0 1
#> 90 20.94 1 50 0 1
#> 23.1 16.92 1 61 0 0
#> 199 19.81 1 NA 0 1
#> 111 17.45 1 47 0 1
#> 93 10.33 1 52 0 1
#> 155.1 13.08 1 26 0 0
#> 90.1 20.94 1 50 0 1
#> 70.1 7.38 1 30 1 0
#> 194.1 22.40 1 38 0 1
#> 8 18.43 1 32 0 0
#> 14 12.89 1 21 0 0
#> 92 22.92 1 47 0 1
#> 145.2 10.07 1 65 1 0
#> 154 12.63 1 20 1 0
#> 179.2 18.63 1 42 0 0
#> 195.2 11.76 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 99.1 21.19 1 38 0 1
#> 55.1 19.34 1 69 0 1
#> 190 20.81 1 42 1 0
#> 180.1 14.82 1 37 0 0
#> 128 20.35 1 35 0 1
#> 181 16.46 1 45 0 1
#> 59 10.16 1 NA 1 0
#> 99.2 21.19 1 38 0 1
#> 41 18.02 1 40 1 0
#> 16 8.71 1 71 0 1
#> 63 22.77 1 31 1 0
#> 26.1 15.77 1 49 0 1
#> 10.1 10.53 1 34 0 0
#> 183.2 9.24 1 67 1 0
#> 41.1 18.02 1 40 1 0
#> 154.1 12.63 1 20 1 0
#> 171.1 16.57 1 41 0 1
#> 30.1 17.43 1 78 0 0
#> 130.1 16.47 1 53 0 1
#> 6.1 15.64 1 39 0 0
#> 15.1 22.68 1 48 0 0
#> 125 15.65 1 67 1 0
#> 61 10.12 1 36 0 1
#> 182 24.00 0 35 0 0
#> 82 24.00 0 34 0 0
#> 21 24.00 0 47 0 0
#> 27 24.00 0 63 1 0
#> 156 24.00 0 50 1 0
#> 147 24.00 0 76 1 0
#> 160 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 82.1 24.00 0 34 0 0
#> 19 24.00 0 57 0 1
#> 193 24.00 0 45 0 1
#> 191 24.00 0 60 0 1
#> 17 24.00 0 38 0 1
#> 22 24.00 0 52 1 0
#> 112 24.00 0 61 0 0
#> 21.1 24.00 0 47 0 0
#> 172 24.00 0 41 0 0
#> 7 24.00 0 37 1 0
#> 147.1 24.00 0 76 1 0
#> 98 24.00 0 34 1 0
#> 19.1 24.00 0 57 0 1
#> 28 24.00 0 67 1 0
#> 112.1 24.00 0 61 0 0
#> 186 24.00 0 45 1 0
#> 162 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 144 24.00 0 28 0 1
#> 64 24.00 0 43 0 0
#> 138 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 27.1 24.00 0 63 1 0
#> 161 24.00 0 45 0 0
#> 94 24.00 0 51 0 1
#> 141 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 156.1 24.00 0 50 1 0
#> 87 24.00 0 27 0 0
#> 62 24.00 0 71 0 0
#> 46.1 24.00 0 71 0 0
#> 34 24.00 0 36 0 0
#> 31 24.00 0 36 0 1
#> 161.1 24.00 0 45 0 0
#> 142 24.00 0 53 0 0
#> 176 24.00 0 43 0 1
#> 87.1 24.00 0 27 0 0
#> 191.1 24.00 0 60 0 1
#> 98.1 24.00 0 34 1 0
#> 67 24.00 0 25 0 0
#> 141.1 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 62.1 24.00 0 71 0 0
#> 141.2 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 182.1 24.00 0 35 0 0
#> 72.1 24.00 0 40 0 1
#> 119 24.00 0 17 0 0
#> 141.3 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 31.1 24.00 0 36 0 1
#> 72.2 24.00 0 40 0 1
#> 53 24.00 0 32 0 1
#> 46.2 24.00 0 71 0 0
#> 191.2 24.00 0 60 0 1
#> 21.2 24.00 0 47 0 0
#> 74 24.00 0 43 0 1
#> 126 24.00 0 48 0 0
#> 2 24.00 0 9 0 0
#> 178 24.00 0 52 1 0
#> 87.2 24.00 0 27 0 0
#> 144.1 24.00 0 28 0 1
#> 17.1 24.00 0 38 0 1
#> 200 24.00 0 64 0 0
#> 176.1 24.00 0 43 0 1
#> 1 24.00 0 23 1 0
#> 9 24.00 0 31 1 0
#> 161.2 24.00 0 45 0 0
#> 35 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 163 24.00 0 66 0 0
#> 33.1 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 65 24.00 0 57 1 0
#> 84.1 24.00 0 39 0 1
#> 126.1 24.00 0 48 0 0
#> 126.2 24.00 0 48 0 0
#> 54 24.00 0 53 1 0
#> 109 24.00 0 48 0 0
#> 71 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.454 NA NA NA
#> 2 age, Cure model 0.00696 NA NA NA
#> 3 grade_ii, Cure model 0.186 NA NA NA
#> 4 grade_iii, Cure model 0.729 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00165 NA NA NA
#> 2 grade_ii, Survival model 0.902 NA NA NA
#> 3 grade_iii, Survival model 0.308 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.453956 0.006959 0.186372 0.728954
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 258.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.453956356 0.006959073 0.186371773 0.728953638
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001652986 0.902151876 0.307543913
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.41414824 0.24455516 0.75067618 0.45310449 0.84715149 0.68522096
#> [7] 0.78336127 0.79959268 0.36453560 0.40427918 0.66015416 0.85489979
#> [13] 0.76706443 0.07465594 0.09129872 0.89261026 0.79153168 0.70995501
#> [19] 0.01152456 0.61746438 0.03342514 0.03342514 0.23213516 0.52782886
#> [25] 0.50941703 0.03342514 0.33433868 0.92263228 0.70995501 0.60007015
#> [31] 0.20537511 0.41414824 0.39435649 0.97949137 0.64328588 0.63473694
#> [37] 0.70175991 0.94431444 0.89261026 0.49087304 0.55542088 0.17939678
#> [43] 0.99318973 0.45310449 0.75067618 0.31233611 0.61746438 0.13851608
#> [49] 0.33433868 0.85489979 0.35435461 0.92263228 0.60007015 0.57334971
#> [55] 0.97248577 0.21886407 0.70995501 0.94431444 0.87754355 0.73432004
#> [61] 0.76706443 0.82371675 0.54630256 0.16531650 0.64328588 0.86998471
#> [67] 0.27859918 0.52782886 0.50016724 0.90761416 0.79959268 0.27859918
#> [73] 0.97949137 0.17939678 0.44319221 0.81564699 0.10828777 0.92263228
#> [79] 0.83168999 0.41414824 0.37464133 0.24455516 0.37464133 0.30130919
#> [85] 0.73432004 0.32339044 0.59114173 0.24455516 0.47248163 0.96541220
#> [91] 0.12462106 0.66015416 0.87754355 0.94431444 0.47248163 0.83168999
#> [97] 0.55542088 0.50941703 0.57334971 0.68522096 0.13851608 0.67691358
#> [103] 0.91513189 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 179 99 133 108 42 6 13 155 170 97 26 107 57
#> 18.63 21.19 14.65 18.29 12.43 15.64 14.34 13.08 19.54 19.14 15.77 11.18 14.46
#> 86 168 52 60 157 24 5 78 78.1 197 23 30 78.2
#> 23.81 23.72 10.42 13.15 15.10 23.89 16.43 23.88 23.88 21.60 16.92 17.43 23.88
#> 158 145 157.1 192 175 179.1 76 70 188 79 18 183 52.1
#> 20.14 10.07 15.10 16.44 21.91 18.63 19.22 7.38 16.16 16.23 15.21 9.24 10.42
#> 184 171 194 25 108.1 133.1 68 5.1 15 158.1 107.1 105 145.1
#> 17.77 16.57 22.40 6.32 18.29 14.65 20.62 16.43 22.68 20.14 11.18 19.75 10.07
#> 85 130 149 136 157.2 183.1 10 180 57.1 140 106 169 188.1
#> 16.44 16.47 8.37 21.83 15.10 9.24 10.53 14.82 14.46 12.68 16.67 22.41 16.16
#> 159 90 23.1 111 93 155.1 90.1 70.1 194.1 8 14 92 145.2
#> 10.55 20.94 16.92 17.45 10.33 13.08 20.94 7.38 22.40 18.43 12.89 22.92 10.07
#> 154 179.2 55 99.1 55.1 190 180.1 128 181 99.2 41 16 63
#> 12.63 18.63 19.34 21.19 19.34 20.81 14.82 20.35 16.46 21.19 18.02 8.71 22.77
#> 26.1 10.1 183.2 41.1 154.1 171.1 30.1 130.1 6.1 15.1 125 61 182
#> 15.77 10.53 9.24 18.02 12.63 16.57 17.43 16.47 15.64 22.68 15.65 10.12 24.00
#> 82 21 27 156 147 160 72 82.1 19 193 191 17 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 21.1 172 7 147.1 98 19.1 28 112.1 186 162 20 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 138 46 27.1 161 94 141 33 156.1 87 62 46.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 161.1 142 176 87.1 191.1 98.1 67 141.1 165 62.1 141.2 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.1 72.1 119 141.3 118 31.1 72.2 53 46.2 191.2 21.2 74 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 178 87.2 144.1 17.1 200 176.1 1 9 161.2 35 151 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 148 65 84.1 126.1 126.2 54 109 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[77]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01029193 0.41136239 0.29117317
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.317709724 0.006497679 0.177447203
#> grade_iii, Cure model
#> 0.653717693
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 59 10.16 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 68 20.62 1 44 0 0
#> 8 18.43 1 32 0 0
#> 15 22.68 1 48 0 0
#> 24 23.89 1 38 0 0
#> 149 8.37 1 33 1 0
#> 117 17.46 1 26 0 1
#> 43 12.10 1 61 0 1
#> 23 16.92 1 61 0 0
#> 96 14.54 1 33 0 1
#> 68.1 20.62 1 44 0 0
#> 63 22.77 1 31 1 0
#> 149.1 8.37 1 33 1 0
#> 32 20.90 1 37 1 0
#> 197 21.60 1 69 1 0
#> 150 20.33 1 48 0 0
#> 124 9.73 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 171 16.57 1 41 0 1
#> 190 20.81 1 42 1 0
#> 91 5.33 1 61 0 1
#> 190.1 20.81 1 42 1 0
#> 55 19.34 1 69 0 1
#> 129 23.41 1 53 1 0
#> 190.2 20.81 1 42 1 0
#> 51 18.23 1 83 0 1
#> 93 10.33 1 52 0 1
#> 139 21.49 1 63 1 0
#> 125 15.65 1 67 1 0
#> 169 22.41 1 46 0 0
#> 140 12.68 1 59 1 0
#> 40 18.00 1 28 1 0
#> 96.1 14.54 1 33 0 1
#> 187 9.92 1 39 1 0
#> 79 16.23 1 54 1 0
#> 96.2 14.54 1 33 0 1
#> 113 22.86 1 34 0 0
#> 177 12.53 1 75 0 0
#> 42 12.43 1 49 0 1
#> 192 16.44 1 31 1 0
#> 159 10.55 1 50 0 1
#> 154 12.63 1 20 1 0
#> 168 23.72 1 70 0 0
#> 10 10.53 1 34 0 0
#> 128 20.35 1 35 0 1
#> 16 8.71 1 71 0 1
#> 154.1 12.63 1 20 1 0
#> 136 21.83 1 43 0 1
#> 70 7.38 1 30 1 0
#> 145 10.07 1 65 1 0
#> 183 9.24 1 67 1 0
#> 30 17.43 1 78 0 0
#> 133 14.65 1 57 0 0
#> 86 23.81 1 58 0 1
#> 177.1 12.53 1 75 0 0
#> 187.1 9.92 1 39 1 0
#> 85 16.44 1 36 0 0
#> 39 15.59 1 37 0 1
#> 49 12.19 1 48 1 0
#> 85.1 16.44 1 36 0 0
#> 154.2 12.63 1 20 1 0
#> 86.1 23.81 1 58 0 1
#> 128.1 20.35 1 35 0 1
#> 39.1 15.59 1 37 0 1
#> 29 15.45 1 68 1 0
#> 101 9.97 1 10 0 1
#> 136.1 21.83 1 43 0 1
#> 49.1 12.19 1 48 1 0
#> 195 11.76 1 NA 1 0
#> 39.2 15.59 1 37 0 1
#> 39.3 15.59 1 37 0 1
#> 14 12.89 1 21 0 0
#> 128.2 20.35 1 35 0 1
#> 18 15.21 1 49 1 0
#> 101.1 9.97 1 10 0 1
#> 76 19.22 1 54 0 1
#> 192.1 16.44 1 31 1 0
#> 79.1 16.23 1 54 1 0
#> 70.1 7.38 1 30 1 0
#> 50 10.02 1 NA 1 0
#> 93.1 10.33 1 52 0 1
#> 133.1 14.65 1 57 0 0
#> 97 19.14 1 65 0 1
#> 37 12.52 1 57 1 0
#> 181 16.46 1 45 0 1
#> 159.1 10.55 1 50 0 1
#> 70.2 7.38 1 30 1 0
#> 14.1 12.89 1 21 0 0
#> 49.2 12.19 1 48 1 0
#> 23.1 16.92 1 61 0 0
#> 157 15.10 1 47 0 0
#> 18.1 15.21 1 49 1 0
#> 194 22.40 1 38 0 1
#> 181.1 16.46 1 45 0 1
#> 10.1 10.53 1 34 0 0
#> 123 13.00 1 44 1 0
#> 117.1 17.46 1 26 0 1
#> 96.3 14.54 1 33 0 1
#> 184 17.77 1 38 0 0
#> 32.1 20.90 1 37 1 0
#> 68.2 20.62 1 44 0 0
#> 167 15.55 1 56 1 0
#> 57 14.46 1 45 0 1
#> 180 14.82 1 37 0 0
#> 129.1 23.41 1 53 1 0
#> 189 10.51 1 NA 1 0
#> 39.4 15.59 1 37 0 1
#> 93.2 10.33 1 52 0 1
#> 130 16.47 1 53 0 1
#> 123.1 13.00 1 44 1 0
#> 140.1 12.68 1 59 1 0
#> 33 24.00 0 53 0 0
#> 115 24.00 0 NA 1 0
#> 94 24.00 0 51 0 1
#> 200 24.00 0 64 0 0
#> 178 24.00 0 52 1 0
#> 48 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 2 24.00 0 9 0 0
#> 115.1 24.00 0 NA 1 0
#> 138 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 94.1 24.00 0 51 0 1
#> 146 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 80 24.00 0 41 0 0
#> 163 24.00 0 66 0 0
#> 142 24.00 0 53 0 0
#> 84 24.00 0 39 0 1
#> 2.1 24.00 0 9 0 0
#> 48.1 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 193 24.00 0 45 0 1
#> 186.1 24.00 0 45 1 0
#> 44 24.00 0 56 0 0
#> 28 24.00 0 67 1 0
#> 62 24.00 0 71 0 0
#> 173 24.00 0 19 0 1
#> 72 24.00 0 40 0 1
#> 116.1 24.00 0 58 0 1
#> 141.1 24.00 0 44 1 0
#> 72.1 24.00 0 40 0 1
#> 137 24.00 0 45 1 0
#> 67.1 24.00 0 25 0 0
#> 94.2 24.00 0 51 0 1
#> 137.1 24.00 0 45 1 0
#> 178.1 24.00 0 52 1 0
#> 178.2 24.00 0 52 1 0
#> 116.2 24.00 0 58 0 1
#> 156 24.00 0 50 1 0
#> 137.2 24.00 0 45 1 0
#> 196 24.00 0 19 0 0
#> 142.1 24.00 0 53 0 0
#> 2.2 24.00 0 9 0 0
#> 21 24.00 0 47 0 0
#> 116.3 24.00 0 58 0 1
#> 191 24.00 0 60 0 1
#> 143 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 2.3 24.00 0 9 0 0
#> 11 24.00 0 42 0 1
#> 185 24.00 0 44 1 0
#> 102 24.00 0 49 0 0
#> 27.1 24.00 0 63 1 0
#> 98 24.00 0 34 1 0
#> 143.1 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 9 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 53 24.00 0 32 0 1
#> 80.1 24.00 0 41 0 0
#> 144.1 24.00 0 28 0 1
#> 73.1 24.00 0 NA 0 1
#> 104 24.00 0 50 1 0
#> 102.1 24.00 0 49 0 0
#> 38 24.00 0 31 1 0
#> 53.1 24.00 0 32 0 1
#> 147 24.00 0 76 1 0
#> 84.1 24.00 0 39 0 1
#> 83 24.00 0 6 0 0
#> 148 24.00 0 61 1 0
#> 75.1 24.00 0 21 1 0
#> 34 24.00 0 36 0 0
#> 75.2 24.00 0 21 1 0
#> 132 24.00 0 55 0 0
#> 137.3 24.00 0 45 1 0
#> 148.1 24.00 0 61 1 0
#> 31 24.00 0 36 0 1
#> 20 24.00 0 46 1 0
#> 103 24.00 0 56 1 0
#> 163.1 24.00 0 66 0 0
#> 144.2 24.00 0 28 0 1
#> 2.4 24.00 0 9 0 0
#> 112 24.00 0 61 0 0
#> 147.1 24.00 0 76 1 0
#> 151 24.00 0 42 0 0
#> 185.1 24.00 0 44 1 0
#> 178.3 24.00 0 52 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.318 NA NA NA
#> 2 age, Cure model 0.00650 NA NA NA
#> 3 grade_ii, Cure model 0.177 NA NA NA
#> 4 grade_iii, Cure model 0.654 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0103 NA NA NA
#> 2 grade_ii, Survival model 0.411 NA NA NA
#> 3 grade_iii, Survival model 0.291 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.317710 0.006498 0.177447 0.653718
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262
#> Residual Deviance: 258.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.317709724 0.006497679 0.177447203 0.653717693
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01029193 0.41136239 0.29117317
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.095171807 0.140644799 0.231213245 0.043614326 0.001188545 0.934068709
#> [7] 0.267586824 0.769824346 0.294943213 0.549641355 0.140644799 0.037104614
#> [13] 0.934068709 0.103144327 0.079564157 0.188083027 0.196535460 0.313850894
#> [19] 0.118407065 0.988914256 0.118407065 0.196535460 0.019320440 0.118407065
#> [25] 0.240192104 0.824110350 0.087294193 0.410057853 0.050527521 0.642902079
#> [31] 0.249317858 0.549641355 0.889940243 0.390455768 0.549641355 0.030485972
#> [37] 0.695162618 0.727141288 0.352485731 0.780659168 0.664042201 0.013220900
#> [43] 0.802297895 0.164246859 0.922951352 0.664042201 0.065197958 0.956132305
#> [49] 0.856891621 0.911881423 0.285616369 0.528898965 0.005213891 0.695162618
#> [55] 0.889940243 0.352485731 0.420037558 0.737901824 0.352485731 0.664042201
#> [61] 0.005213891 0.164246859 0.420037558 0.478157493 0.867993666 0.065197958
#> [67] 0.737901824 0.420037558 0.420037558 0.621884936 0.164246859 0.488275607
#> [73] 0.867993666 0.213559450 0.352485731 0.390455768 0.956132305 0.824110350
#> [79] 0.528898965 0.222331203 0.716411232 0.333189497 0.780659168 0.956132305
#> [85] 0.621884936 0.737901824 0.294943213 0.508375439 0.488275607 0.057817928
#> [91] 0.333189497 0.802297895 0.601005005 0.267586824 0.549641355 0.258400072
#> [97] 0.103144327 0.140644799 0.468092758 0.590487768 0.518605048 0.019320440
#> [103] 0.420037558 0.824110350 0.323487739 0.601005005 0.642902079 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 153 68 8 15 24 149 117 43 23 96 68.1 63 149.1
#> 21.33 20.62 18.43 22.68 23.89 8.37 17.46 12.10 16.92 14.54 20.62 22.77 8.37
#> 32 197 150 58 171 190 91 190.1 55 129 190.2 51 93
#> 20.90 21.60 20.33 19.34 16.57 20.81 5.33 20.81 19.34 23.41 20.81 18.23 10.33
#> 139 125 169 140 40 96.1 187 79 96.2 113 177 42 192
#> 21.49 15.65 22.41 12.68 18.00 14.54 9.92 16.23 14.54 22.86 12.53 12.43 16.44
#> 159 154 168 10 128 16 154.1 136 70 145 183 30 133
#> 10.55 12.63 23.72 10.53 20.35 8.71 12.63 21.83 7.38 10.07 9.24 17.43 14.65
#> 86 177.1 187.1 85 39 49 85.1 154.2 86.1 128.1 39.1 29 101
#> 23.81 12.53 9.92 16.44 15.59 12.19 16.44 12.63 23.81 20.35 15.59 15.45 9.97
#> 136.1 49.1 39.2 39.3 14 128.2 18 101.1 76 192.1 79.1 70.1 93.1
#> 21.83 12.19 15.59 15.59 12.89 20.35 15.21 9.97 19.22 16.44 16.23 7.38 10.33
#> 133.1 97 37 181 159.1 70.2 14.1 49.2 23.1 157 18.1 194 181.1
#> 14.65 19.14 12.52 16.46 10.55 7.38 12.89 12.19 16.92 15.10 15.21 22.40 16.46
#> 10.1 123 117.1 96.3 184 32.1 68.2 167 57 180 129.1 39.4 93.2
#> 10.53 13.00 17.46 14.54 17.77 20.90 20.62 15.55 14.46 14.82 23.41 15.59 10.33
#> 130 123.1 140.1 33 94 200 178 48 75 2 138 186 94.1
#> 16.47 13.00 12.68 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 116 80 163 142 84 2.1 48.1 141 67 193 186.1 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 62 173 72 116.1 141.1 72.1 137 67.1 94.2 137.1 178.1 178.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.2 156 137.2 196 142.1 2.2 21 116.3 191 143 27 2.3 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 102 27.1 98 143.1 9 144 53 80.1 144.1 104 102.1 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.1 147 84.1 83 148 75.1 34 75.2 132 137.3 148.1 31 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 163.1 144.2 2.4 112 147.1 151 185.1 178.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[78]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002829766 0.346817323 0.433421177
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.93726226 0.02176341 0.03772338
#> grade_iii, Cure model
#> 0.11053370
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 77 7.27 1 67 0 1
#> 157 15.10 1 47 0 0
#> 88 18.37 1 47 0 0
#> 41 18.02 1 40 1 0
#> 15 22.68 1 48 0 0
#> 129 23.41 1 53 1 0
#> 171 16.57 1 41 0 1
#> 37 12.52 1 57 1 0
#> 56 12.21 1 60 0 0
#> 192 16.44 1 31 1 0
#> 29 15.45 1 68 1 0
#> 157.1 15.10 1 47 0 0
#> 4 17.64 1 NA 0 1
#> 153 21.33 1 55 1 0
#> 85 16.44 1 36 0 0
#> 39 15.59 1 37 0 1
#> 68 20.62 1 44 0 0
#> 140 12.68 1 59 1 0
#> 189 10.51 1 NA 1 0
#> 153.1 21.33 1 55 1 0
#> 168 23.72 1 70 0 0
#> 78 23.88 1 43 0 0
#> 57 14.46 1 45 0 1
#> 184 17.77 1 38 0 0
#> 93 10.33 1 52 0 1
#> 195 11.76 1 NA 1 0
#> 157.2 15.10 1 47 0 0
#> 155 13.08 1 26 0 0
#> 76 19.22 1 54 0 1
#> 158 20.14 1 74 1 0
#> 114 13.68 1 NA 0 0
#> 8 18.43 1 32 0 0
#> 183 9.24 1 67 1 0
#> 88.1 18.37 1 47 0 0
#> 107 11.18 1 54 1 0
#> 197 21.60 1 69 1 0
#> 10 10.53 1 34 0 0
#> 195.1 11.76 1 NA 1 0
#> 129.1 23.41 1 53 1 0
#> 154 12.63 1 20 1 0
#> 97 19.14 1 65 0 1
#> 63 22.77 1 31 1 0
#> 195.2 11.76 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 13 14.34 1 54 0 1
#> 13.1 14.34 1 54 0 1
#> 51 18.23 1 83 0 1
#> 24 23.89 1 38 0 0
#> 15.1 22.68 1 48 0 0
#> 25 6.32 1 34 1 0
#> 16 8.71 1 71 0 1
#> 40 18.00 1 28 1 0
#> 195.3 11.76 1 NA 1 0
#> 184.1 17.77 1 38 0 0
#> 32 20.90 1 37 1 0
#> 49 12.19 1 48 1 0
#> 175 21.91 1 43 0 0
#> 136 21.83 1 43 0 1
#> 93.1 10.33 1 52 0 1
#> 39.1 15.59 1 37 0 1
#> 124 9.73 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 81 14.06 1 34 0 0
#> 179 18.63 1 42 0 0
#> 86 23.81 1 58 0 1
#> 39.2 15.59 1 37 0 1
#> 134 17.81 1 47 1 0
#> 125 15.65 1 67 1 0
#> 30 17.43 1 78 0 0
#> 106 16.67 1 49 1 0
#> 170 19.54 1 43 0 1
#> 177 12.53 1 75 0 0
#> 133 14.65 1 57 0 0
#> 195.4 11.76 1 NA 1 0
#> 106.1 16.67 1 49 1 0
#> 41.1 18.02 1 40 1 0
#> 189.1 10.51 1 NA 1 0
#> 85.1 16.44 1 36 0 0
#> 149 8.37 1 33 1 0
#> 170.1 19.54 1 43 0 1
#> 97.1 19.14 1 65 0 1
#> 51.1 18.23 1 83 0 1
#> 128 20.35 1 35 0 1
#> 16.1 8.71 1 71 0 1
#> 43 12.10 1 61 0 1
#> 37.1 12.52 1 57 1 0
#> 56.1 12.21 1 60 0 0
#> 40.1 18.00 1 28 1 0
#> 59 10.16 1 NA 1 0
#> 157.3 15.10 1 47 0 0
#> 101 9.97 1 10 0 1
#> 100 16.07 1 60 0 0
#> 117 17.46 1 26 0 1
#> 145 10.07 1 65 1 0
#> 39.3 15.59 1 37 0 1
#> 125.1 15.65 1 67 1 0
#> 57.1 14.46 1 45 0 1
#> 133.1 14.65 1 57 0 0
#> 107.1 11.18 1 54 1 0
#> 100.1 16.07 1 60 0 0
#> 91 5.33 1 61 0 1
#> 43.1 12.10 1 61 0 1
#> 108 18.29 1 39 0 1
#> 68.1 20.62 1 44 0 0
#> 85.2 16.44 1 36 0 0
#> 37.2 12.52 1 57 1 0
#> 55 19.34 1 69 0 1
#> 79 16.23 1 54 1 0
#> 66 22.13 1 53 0 0
#> 113 22.86 1 34 0 0
#> 90 20.94 1 50 0 1
#> 29.1 15.45 1 68 1 0
#> 74 24.00 0 43 0 1
#> 54 24.00 0 53 1 0
#> 200 24.00 0 64 0 0
#> 142 24.00 0 53 0 0
#> 20 24.00 0 46 1 0
#> 71 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 35 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#> 185 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 3 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 38 24.00 0 31 1 0
#> 142.1 24.00 0 53 0 0
#> 75 24.00 0 21 1 0
#> 17 24.00 0 38 0 1
#> 152.1 24.00 0 36 0 1
#> 71.1 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 156 24.00 0 50 1 0
#> 35.1 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 146 24.00 0 63 1 0
#> 131 24.00 0 66 0 0
#> 98 24.00 0 34 1 0
#> 118 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 144 24.00 0 28 0 1
#> 165 24.00 0 47 0 0
#> 87 24.00 0 27 0 0
#> 95 24.00 0 68 0 1
#> 173 24.00 0 19 0 1
#> 53 24.00 0 32 0 1
#> 122 24.00 0 66 0 0
#> 151 24.00 0 42 0 0
#> 3.1 24.00 0 31 1 0
#> 54.1 24.00 0 53 1 0
#> 75.1 24.00 0 21 1 0
#> 152.2 24.00 0 36 0 1
#> 109 24.00 0 48 0 0
#> 98.1 24.00 0 34 1 0
#> 116 24.00 0 58 0 1
#> 191 24.00 0 60 0 1
#> 156.1 24.00 0 50 1 0
#> 118.1 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 33 24.00 0 53 0 0
#> 112 24.00 0 61 0 0
#> 1 24.00 0 23 1 0
#> 173.1 24.00 0 19 0 1
#> 116.1 24.00 0 58 0 1
#> 161 24.00 0 45 0 0
#> 126 24.00 0 48 0 0
#> 72 24.00 0 40 0 1
#> 151.1 24.00 0 42 0 0
#> 182 24.00 0 35 0 0
#> 35.2 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 80 24.00 0 41 0 0
#> 84.1 24.00 0 39 0 1
#> 28.1 24.00 0 67 1 0
#> 198 24.00 0 66 0 1
#> 20.1 24.00 0 46 1 0
#> 118.2 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 53.1 24.00 0 32 0 1
#> 54.2 24.00 0 53 1 0
#> 11.1 24.00 0 42 0 1
#> 75.2 24.00 0 21 1 0
#> 104 24.00 0 50 1 0
#> 46 24.00 0 71 0 0
#> 198.1 24.00 0 66 0 1
#> 172 24.00 0 41 0 0
#> 34 24.00 0 36 0 0
#> 115 24.00 0 NA 1 0
#> 185.1 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 72.1 24.00 0 40 0 1
#> 109.1 24.00 0 48 0 0
#> 173.2 24.00 0 19 0 1
#> 54.3 24.00 0 53 1 0
#> 198.2 24.00 0 66 0 1
#> 142.2 24.00 0 53 0 0
#> 94 24.00 0 51 0 1
#> 142.3 24.00 0 53 0 0
#> 12 24.00 0 63 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.937 NA NA NA
#> 2 age, Cure model 0.0218 NA NA NA
#> 3 grade_ii, Cure model 0.0377 NA NA NA
#> 4 grade_iii, Cure model 0.111 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00283 NA NA NA
#> 2 grade_ii, Survival model 0.347 NA NA NA
#> 3 grade_iii, Survival model 0.433 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.93726 0.02176 0.03772 0.11053
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.6
#> Residual Deviance: 255.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.93726226 0.02176341 0.03772338 0.11053370
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002829766 0.346817323 0.433421177
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.98034622 0.73863790 0.45875646 0.50639947 0.18283142 0.11939851
#> [7] 0.60316108 0.84962375 0.87083026 0.62000597 0.72342457 0.73863790
#> [13] 0.26965620 0.62000597 0.69286341 0.31909227 0.82781480 0.26965620
#> [19] 0.09879626 0.04944898 0.78364458 0.55116098 0.92662033 0.73863790
#> [25] 0.82047576 0.40890423 0.35422704 0.44885967 0.95376254 0.45875646
#> [31] 0.90595380 0.25600960 0.91971768 0.11939851 0.83511040 0.41927584
#> [37] 0.16723042 0.36560825 0.79849664 0.79849664 0.48790670 0.02014373
#> [43] 0.18283142 0.98692566 0.96048807 0.52450614 0.55116098 0.30701096
#> [49] 0.88498325 0.22698279 0.24181902 0.92662033 0.69286341 0.61162946
#> [55] 0.81313170 0.43894217 0.07723009 0.69286341 0.54228685 0.67690320
#> [61] 0.57745259 0.58616977 0.37693818 0.84237447 0.76857780 0.58616977
#> [67] 0.50639947 0.62000597 0.97372837 0.37693818 0.41927584 0.48790670
#> [73] 0.34256714 0.96048807 0.89205306 0.84962375 0.87083026 0.52450614
#> [79] 0.73863790 0.94700318 0.66067134 0.56870278 0.94021538 0.69286341
#> [85] 0.67690320 0.78364458 0.76857780 0.90595380 0.66067134 0.99348075
#> [91] 0.89205306 0.47821850 0.31909227 0.62000597 0.84962375 0.39831860
#> [97] 0.65246742 0.21202042 0.15079684 0.29465220 0.72342457 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 77 157 88 41 15 129 171 37 56 192 29 157.1 153
#> 7.27 15.10 18.37 18.02 22.68 23.41 16.57 12.52 12.21 16.44 15.45 15.10 21.33
#> 85 39 68 140 153.1 168 78 57 184 93 157.2 155 76
#> 16.44 15.59 20.62 12.68 21.33 23.72 23.88 14.46 17.77 10.33 15.10 13.08 19.22
#> 158 8 183 88.1 107 197 10 129.1 154 97 63 166 13
#> 20.14 18.43 9.24 18.37 11.18 21.60 10.53 23.41 12.63 19.14 22.77 19.98 14.34
#> 13.1 51 24 15.1 25 16 40 184.1 32 49 175 136 93.1
#> 14.34 18.23 23.89 22.68 6.32 8.71 18.00 17.77 20.90 12.19 21.91 21.83 10.33
#> 39.1 130 81 179 86 39.2 134 125 30 106 170 177 133
#> 15.59 16.47 14.06 18.63 23.81 15.59 17.81 15.65 17.43 16.67 19.54 12.53 14.65
#> 106.1 41.1 85.1 149 170.1 97.1 51.1 128 16.1 43 37.1 56.1 40.1
#> 16.67 18.02 16.44 8.37 19.54 19.14 18.23 20.35 8.71 12.10 12.52 12.21 18.00
#> 157.3 101 100 117 145 39.3 125.1 57.1 133.1 107.1 100.1 91 43.1
#> 15.10 9.97 16.07 17.46 10.07 15.59 15.65 14.46 14.65 11.18 16.07 5.33 12.10
#> 108 68.1 85.2 37.2 55 79 66 113 90 29.1 74 54 200
#> 18.29 20.62 16.44 12.52 19.34 16.23 22.13 22.86 20.94 15.45 24.00 24.00 24.00
#> 142 20 71 152 35 102 185 31 3 11 38 142.1 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 152.1 71.1 44 156 35.1 28 146 131 98 118 84 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 87 95 173 53 122 151 3.1 54.1 75.1 152.2 109 98.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 191 156.1 118.1 9 47 33 112 1 173.1 116.1 161 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 151.1 182 35.2 27 80 84.1 28.1 198 20.1 118.2 21 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54.2 11.1 75.2 104 46 198.1 172 34 185.1 135 72.1 109.1 173.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54.3 198.2 142.2 94 142.3 12
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[79]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.004896953 0.664988418 0.497475572
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.89594544 0.01822242 -0.10800983
#> grade_iii, Cure model
#> 0.98978011
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 167 15.55 1 56 1 0
#> 41 18.02 1 40 1 0
#> 190 20.81 1 42 1 0
#> 179 18.63 1 42 0 0
#> 100 16.07 1 60 0 0
#> 90 20.94 1 50 0 1
#> 130 16.47 1 53 0 1
#> 52 10.42 1 52 0 1
#> 42 12.43 1 49 0 1
#> 159 10.55 1 50 0 1
#> 92 22.92 1 47 0 1
#> 85 16.44 1 36 0 0
#> 150 20.33 1 48 0 0
#> 130.1 16.47 1 53 0 1
#> 51 18.23 1 83 0 1
#> 5 16.43 1 51 0 1
#> 108 18.29 1 39 0 1
#> 166 19.98 1 48 0 0
#> 140 12.68 1 59 1 0
#> 18 15.21 1 49 1 0
#> 41.1 18.02 1 40 1 0
#> 113 22.86 1 34 0 0
#> 101 9.97 1 10 0 1
#> 91 5.33 1 61 0 1
#> 96 14.54 1 33 0 1
#> 179.1 18.63 1 42 0 0
#> 91.1 5.33 1 61 0 1
#> 171 16.57 1 41 0 1
#> 149 8.37 1 33 1 0
#> 25 6.32 1 34 1 0
#> 25.1 6.32 1 34 1 0
#> 78 23.88 1 43 0 0
#> 18.1 15.21 1 49 1 0
#> 127 3.53 1 62 0 1
#> 26 15.77 1 49 0 1
#> 154 12.63 1 20 1 0
#> 91.2 5.33 1 61 0 1
#> 168 23.72 1 70 0 0
#> 16 8.71 1 71 0 1
#> 6 15.64 1 39 0 0
#> 125 15.65 1 67 1 0
#> 100.1 16.07 1 60 0 0
#> 58 19.34 1 39 0 0
#> 127.1 3.53 1 62 0 1
#> 177 12.53 1 75 0 0
#> 101.1 9.97 1 10 0 1
#> 136 21.83 1 43 0 1
#> 91.3 5.33 1 61 0 1
#> 92.1 22.92 1 47 0 1
#> 113.1 22.86 1 34 0 0
#> 90.1 20.94 1 50 0 1
#> 190.1 20.81 1 42 1 0
#> 8 18.43 1 32 0 0
#> 56 12.21 1 60 0 0
#> 96.1 14.54 1 33 0 1
#> 5.1 16.43 1 51 0 1
#> 99 21.19 1 38 0 1
#> 93 10.33 1 52 0 1
#> 184 17.77 1 38 0 0
#> 107 11.18 1 54 1 0
#> 79 16.23 1 54 1 0
#> 66 22.13 1 53 0 0
#> 187 9.92 1 39 1 0
#> 5.2 16.43 1 51 0 1
#> 79.1 16.23 1 54 1 0
#> 79.2 16.23 1 54 1 0
#> 100.2 16.07 1 60 0 0
#> 10 10.53 1 34 0 0
#> 136.1 21.83 1 43 0 1
#> 194 22.40 1 38 0 1
#> 150.1 20.33 1 48 0 0
#> 32 20.90 1 37 1 0
#> 123 13.00 1 44 1 0
#> 153 21.33 1 55 1 0
#> 192 16.44 1 31 1 0
#> 99.1 21.19 1 38 0 1
#> 45 17.42 1 54 0 1
#> 124 9.73 1 NA 1 0
#> 159.1 10.55 1 50 0 1
#> 16.1 8.71 1 71 0 1
#> 76 19.22 1 54 0 1
#> 145 10.07 1 65 1 0
#> 125.1 15.65 1 67 1 0
#> 14 12.89 1 21 0 0
#> 49 12.19 1 48 1 0
#> 79.3 16.23 1 54 1 0
#> 93.1 10.33 1 52 0 1
#> 190.2 20.81 1 42 1 0
#> 56.1 12.21 1 60 0 0
#> 13 14.34 1 54 0 1
#> 52.1 10.42 1 52 0 1
#> 79.4 16.23 1 54 1 0
#> 13.1 14.34 1 54 0 1
#> 70 7.38 1 30 1 0
#> 57 14.46 1 45 0 1
#> 158 20.14 1 74 1 0
#> 130.2 16.47 1 53 0 1
#> 13.2 14.34 1 54 0 1
#> 190.3 20.81 1 42 1 0
#> 5.3 16.43 1 51 0 1
#> 10.1 10.53 1 34 0 0
#> 194.1 22.40 1 38 0 1
#> 177.1 12.53 1 75 0 0
#> 192.1 16.44 1 31 1 0
#> 168.1 23.72 1 70 0 0
#> 181 16.46 1 45 0 1
#> 114 13.68 1 NA 0 0
#> 114.1 13.68 1 NA 0 0
#> 136.2 21.83 1 43 0 1
#> 139 21.49 1 63 1 0
#> 79.5 16.23 1 54 1 0
#> 111 17.45 1 47 0 1
#> 7 24.00 0 37 1 0
#> 12 24.00 0 63 0 0
#> 94 24.00 0 51 0 1
#> 19 24.00 0 57 0 1
#> 198 24.00 0 66 0 1
#> 74 24.00 0 43 0 1
#> 138 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 121 24.00 0 57 1 0
#> 122 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 74.1 24.00 0 43 0 1
#> 33 24.00 0 53 0 0
#> 98 24.00 0 34 1 0
#> 178 24.00 0 52 1 0
#> 121.1 24.00 0 57 1 0
#> 191 24.00 0 60 0 1
#> 193 24.00 0 45 0 1
#> 141 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 98.1 24.00 0 34 1 0
#> 196 24.00 0 19 0 0
#> 104 24.00 0 50 1 0
#> 122.1 24.00 0 66 0 0
#> 160 24.00 0 31 1 0
#> 138.1 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 47 24.00 0 38 0 1
#> 33.1 24.00 0 53 0 0
#> 196.1 24.00 0 19 0 0
#> 3 24.00 0 31 1 0
#> 141.1 24.00 0 44 1 0
#> 3.1 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 38 24.00 0 31 1 0
#> 27 24.00 0 63 1 0
#> 152 24.00 0 36 0 1
#> 162 24.00 0 51 0 0
#> 131.1 24.00 0 66 0 0
#> 156 24.00 0 50 1 0
#> 22 24.00 0 52 1 0
#> 174 24.00 0 49 1 0
#> 7.1 24.00 0 37 1 0
#> 173 24.00 0 19 0 1
#> 143 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 2 24.00 0 9 0 0
#> 103 24.00 0 56 1 0
#> 119 24.00 0 17 0 0
#> 9 24.00 0 31 1 0
#> 3.2 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 84 24.00 0 39 0 1
#> 200 24.00 0 64 0 0
#> 104.1 24.00 0 50 1 0
#> 119.1 24.00 0 17 0 0
#> 115 24.00 0 NA 1 0
#> 65 24.00 0 57 1 0
#> 137 24.00 0 45 1 0
#> 152.1 24.00 0 36 0 1
#> 147 24.00 0 76 1 0
#> 53 24.00 0 32 0 1
#> 138.2 24.00 0 44 1 0
#> 7.2 24.00 0 37 1 0
#> 176 24.00 0 43 0 1
#> 147.1 24.00 0 76 1 0
#> 193.1 24.00 0 45 0 1
#> 185 24.00 0 44 1 0
#> 141.2 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 102 24.00 0 49 0 0
#> 46 24.00 0 71 0 0
#> 72 24.00 0 40 0 1
#> 98.2 24.00 0 34 1 0
#> 126 24.00 0 48 0 0
#> 82 24.00 0 34 0 0
#> 98.3 24.00 0 34 1 0
#> 73 24.00 0 NA 0 1
#> 186 24.00 0 45 1 0
#> 104.2 24.00 0 50 1 0
#> 2.1 24.00 0 9 0 0
#> 144 24.00 0 28 0 1
#> 143.1 24.00 0 51 0 0
#> 119.2 24.00 0 17 0 0
#> 19.1 24.00 0 57 0 1
#> 103.1 24.00 0 56 1 0
#> 132 24.00 0 55 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.896 NA NA NA
#> 2 age, Cure model 0.0182 NA NA NA
#> 3 grade_ii, Cure model -0.108 NA NA NA
#> 4 grade_iii, Cure model 0.990 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00490 NA NA NA
#> 2 grade_ii, Survival model 0.665 NA NA NA
#> 3 grade_iii, Survival model 0.497 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.89595 0.01822 -0.10801 0.98978
#>
#> Degrees of Freedom: 194 Total (i.e. Null); 191 Residual
#> Null Deviance: 267.6
#> Residual Deviance: 253.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.89594544 0.01822242 -0.10800983 0.98978011
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.004896953 0.664988418 0.497475572
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.77329164 0.56603511 0.42786356 0.52180944 0.73042073 0.39365643
#> [7] 0.61474358 0.90415951 0.85716395 0.88361082 0.15788206 0.64464211
#> [13] 0.46575100 0.61474358 0.55741609 0.66612962 0.54859670 0.49421632
#> [19] 0.83558031 0.77924368 0.56603511 0.20153743 0.92927787 0.97263859
#> [25] 0.79084254 0.52180944 0.97263859 0.60684506 0.95366426 0.96323846
#> [31] 0.96323846 0.04286930 0.77924368 0.99092005 0.74904317 0.84103011
#> [37] 0.97263859 0.09637811 0.94402205 0.76726735 0.75524628 0.73042073
#> [43] 0.50350017 0.99092005 0.84643980 0.92927787 0.29781579 0.97263859
#> [49] 0.15788206 0.20153743 0.39365643 0.42786356 0.53963460 0.86250635
#> [55] 0.79084254 0.66612962 0.36910525 0.91429414 0.58246415 0.87838611
#> [61] 0.69333192 0.27956528 0.93912192 0.66612962 0.69333192 0.69333192
#> [67] 0.73042073 0.89389586 0.29781579 0.24358420 0.46575100 0.41663120
#> [73] 0.82456209 0.35573126 0.64464211 0.36910525 0.59884131 0.88361082
#> [79] 0.94402205 0.51274815 0.92430433 0.75524628 0.83007318 0.87311331
#> [85] 0.69333192 0.91429414 0.42786356 0.86250635 0.80798369 0.90415951
#> [91] 0.69333192 0.80798369 0.95846633 0.80228482 0.48488603 0.61474358
#> [97] 0.80798369 0.42786356 0.66612962 0.89389586 0.24358420 0.84643980
#> [103] 0.64464211 0.09637811 0.63717024 0.29781579 0.34153244 0.69333192
#> [109] 0.59071346 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 167 41 190 179 100 90 130 52 42 159 92 85 150
#> 15.55 18.02 20.81 18.63 16.07 20.94 16.47 10.42 12.43 10.55 22.92 16.44 20.33
#> 130.1 51 5 108 166 140 18 41.1 113 101 91 96 179.1
#> 16.47 18.23 16.43 18.29 19.98 12.68 15.21 18.02 22.86 9.97 5.33 14.54 18.63
#> 91.1 171 149 25 25.1 78 18.1 127 26 154 91.2 168 16
#> 5.33 16.57 8.37 6.32 6.32 23.88 15.21 3.53 15.77 12.63 5.33 23.72 8.71
#> 6 125 100.1 58 127.1 177 101.1 136 91.3 92.1 113.1 90.1 190.1
#> 15.64 15.65 16.07 19.34 3.53 12.53 9.97 21.83 5.33 22.92 22.86 20.94 20.81
#> 8 56 96.1 5.1 99 93 184 107 79 66 187 5.2 79.1
#> 18.43 12.21 14.54 16.43 21.19 10.33 17.77 11.18 16.23 22.13 9.92 16.43 16.23
#> 79.2 100.2 10 136.1 194 150.1 32 123 153 192 99.1 45 159.1
#> 16.23 16.07 10.53 21.83 22.40 20.33 20.90 13.00 21.33 16.44 21.19 17.42 10.55
#> 16.1 76 145 125.1 14 49 79.3 93.1 190.2 56.1 13 52.1 79.4
#> 8.71 19.22 10.07 15.65 12.89 12.19 16.23 10.33 20.81 12.21 14.34 10.42 16.23
#> 13.1 70 57 158 130.2 13.2 190.3 5.3 10.1 194.1 177.1 192.1 168.1
#> 14.34 7.38 14.46 20.14 16.47 14.34 20.81 16.43 10.53 22.40 12.53 16.44 23.72
#> 181 136.2 139 79.5 111 7 12 94 19 198 74 138 34
#> 16.46 21.83 21.49 16.23 17.45 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 122 48 17 74.1 33 98 178 121.1 191 193 141 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.1 196 104 122.1 160 138.1 146 47 33.1 196.1 3 141.1 3.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 38 27 152 162 131.1 156 22 174 7.1 173 143 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 103 119 9 3.2 1 84 200 104.1 119.1 65 137 152.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 53 138.2 7.2 176 147.1 193.1 185 141.2 112 102 46 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.2 126 82 98.3 186 104.2 2.1 144 143.1 119.2 19.1 103.1 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[80]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001339822 0.978529555 0.679763010
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.42746815 0.03029311 0.21575420
#> grade_iii, Cure model
#> 0.64843515
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 18 15.21 1 49 1 0
#> 76 19.22 1 54 0 1
#> 167 15.55 1 56 1 0
#> 51 18.23 1 83 0 1
#> 192 16.44 1 31 1 0
#> 184 17.77 1 38 0 0
#> 107 11.18 1 54 1 0
#> 183 9.24 1 67 1 0
#> 167.1 15.55 1 56 1 0
#> 43 12.10 1 61 0 1
#> 70 7.38 1 30 1 0
#> 134 17.81 1 47 1 0
#> 183.1 9.24 1 67 1 0
#> 190 20.81 1 42 1 0
#> 158 20.14 1 74 1 0
#> 66 22.13 1 53 0 0
#> 123 13.00 1 44 1 0
#> 140 12.68 1 59 1 0
#> 105 19.75 1 60 0 0
#> 90 20.94 1 50 0 1
#> 159 10.55 1 50 0 1
#> 154 12.63 1 20 1 0
#> 125 15.65 1 67 1 0
#> 153 21.33 1 55 1 0
#> 39 15.59 1 37 0 1
#> 40 18.00 1 28 1 0
#> 154.1 12.63 1 20 1 0
#> 60 13.15 1 38 1 0
#> 78 23.88 1 43 0 0
#> 77 7.27 1 67 0 1
#> 18.1 15.21 1 49 1 0
#> 86 23.81 1 58 0 1
#> 49 12.19 1 48 1 0
#> 190.1 20.81 1 42 1 0
#> 136 21.83 1 43 0 1
#> 50 10.02 1 NA 1 0
#> 77.1 7.27 1 67 0 1
#> 114 13.68 1 NA 0 0
#> 6 15.64 1 39 0 0
#> 181 16.46 1 45 0 1
#> 96 14.54 1 33 0 1
#> 30 17.43 1 78 0 0
#> 25 6.32 1 34 1 0
#> 52 10.42 1 52 0 1
#> 5 16.43 1 51 0 1
#> 96.1 14.54 1 33 0 1
#> 105.1 19.75 1 60 0 0
#> 70.1 7.38 1 30 1 0
#> 6.1 15.64 1 39 0 0
#> 42 12.43 1 49 0 1
#> 179 18.63 1 42 0 0
#> 154.2 12.63 1 20 1 0
#> 194 22.40 1 38 0 1
#> 39.1 15.59 1 37 0 1
#> 153.1 21.33 1 55 1 0
#> 188 16.16 1 46 0 1
#> 79 16.23 1 54 1 0
#> 97 19.14 1 65 0 1
#> 5.1 16.43 1 51 0 1
#> 39.2 15.59 1 37 0 1
#> 111 17.45 1 47 0 1
#> 66.1 22.13 1 53 0 0
#> 42.1 12.43 1 49 0 1
#> 52.1 10.42 1 52 0 1
#> 37 12.52 1 57 1 0
#> 145 10.07 1 65 1 0
#> 105.2 19.75 1 60 0 0
#> 36 21.19 1 48 0 1
#> 69 23.23 1 25 0 1
#> 133 14.65 1 57 0 0
#> 57 14.46 1 45 0 1
#> 60.1 13.15 1 38 1 0
#> 23 16.92 1 61 0 0
#> 32 20.90 1 37 1 0
#> 166 19.98 1 48 0 0
#> 16 8.71 1 71 0 1
#> 49.1 12.19 1 48 1 0
#> 153.2 21.33 1 55 1 0
#> 10 10.53 1 34 0 0
#> 5.2 16.43 1 51 0 1
#> 77.2 7.27 1 67 0 1
#> 114.1 13.68 1 NA 0 0
#> 79.1 16.23 1 54 1 0
#> 129 23.41 1 53 1 0
#> 36.1 21.19 1 48 0 1
#> 190.2 20.81 1 42 1 0
#> 168 23.72 1 70 0 0
#> 150 20.33 1 48 0 0
#> 55 19.34 1 69 0 1
#> 18.2 15.21 1 49 1 0
#> 78.1 23.88 1 43 0 0
#> 150.1 20.33 1 48 0 0
#> 25.1 6.32 1 34 1 0
#> 181.1 16.46 1 45 0 1
#> 78.2 23.88 1 43 0 0
#> 107.1 11.18 1 54 1 0
#> 39.3 15.59 1 37 0 1
#> 39.4 15.59 1 37 0 1
#> 139 21.49 1 63 1 0
#> 58 19.34 1 39 0 0
#> 8 18.43 1 32 0 0
#> 164 23.60 1 76 0 1
#> 24 23.89 1 38 0 0
#> 69.1 23.23 1 25 0 1
#> 123.1 13.00 1 44 1 0
#> 77.3 7.27 1 67 0 1
#> 39.5 15.59 1 37 0 1
#> 81 14.06 1 34 0 0
#> 69.2 23.23 1 25 0 1
#> 57.1 14.46 1 45 0 1
#> 166.1 19.98 1 48 0 0
#> 110 17.56 1 65 0 1
#> 20 24.00 0 46 1 0
#> 53 24.00 0 32 0 1
#> 19 24.00 0 57 0 1
#> 104 24.00 0 50 1 0
#> 135 24.00 0 58 1 0
#> 141 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 173 24.00 0 19 0 1
#> 147 24.00 0 76 1 0
#> 1 24.00 0 23 1 0
#> 1.1 24.00 0 23 1 0
#> 83 24.00 0 6 0 0
#> 142 24.00 0 53 0 0
#> 9 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 121 24.00 0 57 1 0
#> 186 24.00 0 45 1 0
#> 84 24.00 0 39 0 1
#> 119 24.00 0 17 0 0
#> 147.1 24.00 0 76 1 0
#> 176 24.00 0 43 0 1
#> 176.1 24.00 0 43 0 1
#> 75 24.00 0 21 1 0
#> 122.1 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 84.1 24.00 0 39 0 1
#> 196 24.00 0 19 0 0
#> 163 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 82 24.00 0 34 0 0
#> 186.1 24.00 0 45 1 0
#> 200 24.00 0 64 0 0
#> 46 24.00 0 71 0 0
#> 193 24.00 0 45 0 1
#> 173.1 24.00 0 19 0 1
#> 72 24.00 0 40 0 1
#> 186.2 24.00 0 45 1 0
#> 132 24.00 0 55 0 0
#> 121.1 24.00 0 57 1 0
#> 62 24.00 0 71 0 0
#> 73 24.00 0 NA 0 1
#> 163.1 24.00 0 66 0 0
#> 20.1 24.00 0 46 1 0
#> 138 24.00 0 44 1 0
#> 73.1 24.00 0 NA 0 1
#> 144 24.00 0 28 0 1
#> 182 24.00 0 35 0 0
#> 196.1 24.00 0 19 0 0
#> 83.1 24.00 0 6 0 0
#> 118 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 103 24.00 0 56 1 0
#> 84.2 24.00 0 39 0 1
#> 176.2 24.00 0 43 0 1
#> 65 24.00 0 57 1 0
#> 34 24.00 0 36 0 0
#> 1.2 24.00 0 23 1 0
#> 75.1 24.00 0 21 1 0
#> 71 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 75.2 24.00 0 21 1 0
#> 104.1 24.00 0 50 1 0
#> 67 24.00 0 25 0 0
#> 31 24.00 0 36 0 1
#> 144.1 24.00 0 28 0 1
#> 17 24.00 0 38 0 1
#> 135.1 24.00 0 58 1 0
#> 121.2 24.00 0 57 1 0
#> 94 24.00 0 51 0 1
#> 12 24.00 0 63 0 0
#> 72.1 24.00 0 40 0 1
#> 161 24.00 0 45 0 0
#> 19.1 24.00 0 57 0 1
#> 53.1 24.00 0 32 0 1
#> 83.2 24.00 0 6 0 0
#> 118.1 24.00 0 44 1 0
#> 73.2 24.00 0 NA 0 1
#> 74 24.00 0 43 0 1
#> 33 24.00 0 53 0 0
#> 47.1 24.00 0 38 0 1
#> 2 24.00 0 9 0 0
#> 11 24.00 0 42 0 1
#> 132.1 24.00 0 55 0 0
#> 38.1 24.00 0 31 1 0
#> 9.1 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 160 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.43 NA NA NA
#> 2 age, Cure model 0.0303 NA NA NA
#> 3 grade_ii, Cure model 0.216 NA NA NA
#> 4 grade_iii, Cure model 0.648 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00134 NA NA NA
#> 2 grade_ii, Survival model 0.979 NA NA NA
#> 3 grade_iii, Survival model 0.680 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.42747 0.03029 0.21575 0.64844
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266
#> Residual Deviance: 253.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.42746815 0.03029311 0.21575420 0.64843515
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001339822 0.978529555 0.679763010
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.79748112 0.57460552 0.78563659 0.60736208 0.68288609 0.63088258
#> [7] 0.91908673 0.95185274 0.78563659 0.91425823 0.96539263 0.62322022
#> [13] 0.95185274 0.46254102 0.50671420 0.32906066 0.85876574 0.86931132
#> [19] 0.53249151 0.44203185 0.92853422 0.87454041 0.73029607 0.38753369
#> [25] 0.74963770 0.61538116 0.87454041 0.84797881 0.08168168 0.97423367
#> [31] 0.79748112 0.16600623 0.90456845 0.46254102 0.35916303 0.97423367
#> [37] 0.73676624 0.66843839 0.82019223 0.65355018 0.99147459 0.93795142
#> [43] 0.69001413 0.82019223 0.53249151 0.96539263 0.73676624 0.89468415
#> [49] 0.59105967 0.87454041 0.31354262 0.74963770 0.38753369 0.72371451
#> [55] 0.71047957 0.58289953 0.69001413 0.74963770 0.64609315 0.32906066
#> [61] 0.89468415 0.93795142 0.88966673 0.94724010 0.53249151 0.42080211
#> [67] 0.26689553 0.81448690 0.83139813 0.84797881 0.66099786 0.45249499
#> [73] 0.51536767 0.96088878 0.90456845 0.38753369 0.93324337 0.69001413
#> [79] 0.97423367 0.71047957 0.24637977 0.42080211 0.46254102 0.19425726
#> [85] 0.48897298 0.55786825 0.79748112 0.08168168 0.48897298 0.99147459
#> [91] 0.66843839 0.08168168 0.91908673 0.74963770 0.74963770 0.37385755
#> [97] 0.55786825 0.59921331 0.22211768 0.03157825 0.26689553 0.85876574
#> [103] 0.97423367 0.74963770 0.84244091 0.26689553 0.83139813 0.51536767
#> [109] 0.63854008 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000
#>
#> $Time
#> 18 76 167 51 192 184 107 183 167.1 43 70 134 183.1
#> 15.21 19.22 15.55 18.23 16.44 17.77 11.18 9.24 15.55 12.10 7.38 17.81 9.24
#> 190 158 66 123 140 105 90 159 154 125 153 39 40
#> 20.81 20.14 22.13 13.00 12.68 19.75 20.94 10.55 12.63 15.65 21.33 15.59 18.00
#> 154.1 60 78 77 18.1 86 49 190.1 136 77.1 6 181 96
#> 12.63 13.15 23.88 7.27 15.21 23.81 12.19 20.81 21.83 7.27 15.64 16.46 14.54
#> 30 25 52 5 96.1 105.1 70.1 6.1 42 179 154.2 194 39.1
#> 17.43 6.32 10.42 16.43 14.54 19.75 7.38 15.64 12.43 18.63 12.63 22.40 15.59
#> 153.1 188 79 97 5.1 39.2 111 66.1 42.1 52.1 37 145 105.2
#> 21.33 16.16 16.23 19.14 16.43 15.59 17.45 22.13 12.43 10.42 12.52 10.07 19.75
#> 36 69 133 57 60.1 23 32 166 16 49.1 153.2 10 5.2
#> 21.19 23.23 14.65 14.46 13.15 16.92 20.90 19.98 8.71 12.19 21.33 10.53 16.43
#> 77.2 79.1 129 36.1 190.2 168 150 55 18.2 78.1 150.1 25.1 181.1
#> 7.27 16.23 23.41 21.19 20.81 23.72 20.33 19.34 15.21 23.88 20.33 6.32 16.46
#> 78.2 107.1 39.3 39.4 139 58 8 164 24 69.1 123.1 77.3 39.5
#> 23.88 11.18 15.59 15.59 21.49 19.34 18.43 23.60 23.89 23.23 13.00 7.27 15.59
#> 81 69.2 57.1 166.1 110 20 53 19 104 135 141 38 122
#> 14.06 23.23 14.46 19.98 17.56 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 147 1 1.1 83 142 9 47 121 186 84 119 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 176.1 75 122.1 48 84.1 196 163 174 82 186.1 200 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 173.1 72 186.2 132 121.1 62 163.1 20.1 138 144 182 196.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83.1 118 22 103 84.2 176.2 65 34 1.2 75.1 71 44 75.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.1 67 31 144.1 17 135.1 121.2 94 12 72.1 161 19.1 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83.2 118.1 74 33 47.1 2 11 132.1 38.1 9.1 156 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[81]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0026712 0.7188807 0.4009038
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.5699515 0.0141547 -0.3801204
#> grade_iii, Cure model
#> 0.8533958
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 194 22.40 1 38 0 1
#> 41 18.02 1 40 1 0
#> 45 17.42 1 54 0 1
#> 85 16.44 1 36 0 0
#> 169 22.41 1 46 0 0
#> 155 13.08 1 26 0 0
#> 113 22.86 1 34 0 0
#> 25 6.32 1 34 1 0
#> 125 15.65 1 67 1 0
#> 16 8.71 1 71 0 1
#> 69 23.23 1 25 0 1
#> 36 21.19 1 48 0 1
#> 170 19.54 1 43 0 1
#> 168 23.72 1 70 0 0
#> 127 3.53 1 62 0 1
#> 40 18.00 1 28 1 0
#> 171 16.57 1 41 0 1
#> 61 10.12 1 36 0 1
#> 130 16.47 1 53 0 1
#> 55 19.34 1 69 0 1
#> 4 17.64 1 NA 0 1
#> 170.1 19.54 1 43 0 1
#> 100 16.07 1 60 0 0
#> 150 20.33 1 48 0 0
#> 78 23.88 1 43 0 0
#> 26 15.77 1 49 0 1
#> 111 17.45 1 47 0 1
#> 61.1 10.12 1 36 0 1
#> 61.2 10.12 1 36 0 1
#> 60 13.15 1 38 1 0
#> 171.1 16.57 1 41 0 1
#> 15 22.68 1 48 0 0
#> 55.1 19.34 1 69 0 1
#> 110 17.56 1 65 0 1
#> 56 12.21 1 60 0 0
#> 199 19.81 1 NA 0 1
#> 110.1 17.56 1 65 0 1
#> 192 16.44 1 31 1 0
#> 58 19.34 1 39 0 0
#> 175 21.91 1 43 0 0
#> 99 21.19 1 38 0 1
#> 180 14.82 1 37 0 0
#> 128 20.35 1 35 0 1
#> 133 14.65 1 57 0 0
#> 39 15.59 1 37 0 1
#> 150.1 20.33 1 48 0 0
#> 106 16.67 1 49 1 0
#> 68 20.62 1 44 0 0
#> 8 18.43 1 32 0 0
#> 139 21.49 1 63 1 0
#> 61.3 10.12 1 36 0 1
#> 16.1 8.71 1 71 0 1
#> 91 5.33 1 61 0 1
#> 140 12.68 1 59 1 0
#> 14 12.89 1 21 0 0
#> 37 12.52 1 57 1 0
#> 49 12.19 1 48 1 0
#> 145 10.07 1 65 1 0
#> 113.1 22.86 1 34 0 0
#> 79 16.23 1 54 1 0
#> 158 20.14 1 74 1 0
#> 164 23.60 1 76 0 1
#> 66 22.13 1 53 0 0
#> 180.1 14.82 1 37 0 0
#> 197 21.60 1 69 1 0
#> 96 14.54 1 33 0 1
#> 128.1 20.35 1 35 0 1
#> 133.1 14.65 1 57 0 0
#> 180.2 14.82 1 37 0 0
#> 13 14.34 1 54 0 1
#> 123 13.00 1 44 1 0
#> 59 10.16 1 NA 1 0
#> 79.1 16.23 1 54 1 0
#> 66.1 22.13 1 53 0 0
#> 91.1 5.33 1 61 0 1
#> 14.1 12.89 1 21 0 0
#> 29 15.45 1 68 1 0
#> 183 9.24 1 67 1 0
#> 177 12.53 1 75 0 0
#> 41.1 18.02 1 40 1 0
#> 86 23.81 1 58 0 1
#> 5 16.43 1 51 0 1
#> 192.1 16.44 1 31 1 0
#> 179 18.63 1 42 0 0
#> 97 19.14 1 65 0 1
#> 14.2 12.89 1 21 0 0
#> 66.2 22.13 1 53 0 0
#> 81 14.06 1 34 0 0
#> 105 19.75 1 60 0 0
#> 170.2 19.54 1 43 0 1
#> 36.1 21.19 1 48 0 1
#> 60.1 13.15 1 38 1 0
#> 181 16.46 1 45 0 1
#> 110.2 17.56 1 65 0 1
#> 184 17.77 1 38 0 0
#> 13.1 14.34 1 54 0 1
#> 66.3 22.13 1 53 0 0
#> 77 7.27 1 67 0 1
#> 188 16.16 1 46 0 1
#> 183.1 9.24 1 67 1 0
#> 197.1 21.60 1 69 1 0
#> 55.2 19.34 1 69 0 1
#> 63 22.77 1 31 1 0
#> 189 10.51 1 NA 1 0
#> 123.1 13.00 1 44 1 0
#> 184.1 17.77 1 38 0 0
#> 169.1 22.41 1 46 0 0
#> 190 20.81 1 42 1 0
#> 76 19.22 1 54 0 1
#> 37.1 12.52 1 57 1 0
#> 45.1 17.42 1 54 0 1
#> 90 20.94 1 50 0 1
#> 151 24.00 0 42 0 0
#> 182 24.00 0 35 0 0
#> 138 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 103 24.00 0 56 1 0
#> 22 24.00 0 52 1 0
#> 11 24.00 0 42 0 1
#> 12 24.00 0 63 0 0
#> 104 24.00 0 50 1 0
#> 156 24.00 0 50 1 0
#> 34 24.00 0 36 0 0
#> 53 24.00 0 32 0 1
#> 9 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 182.1 24.00 0 35 0 0
#> 144 24.00 0 28 0 1
#> 135 24.00 0 58 1 0
#> 7 24.00 0 37 1 0
#> 64 24.00 0 43 0 0
#> 31 24.00 0 36 0 1
#> 141 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 54 24.00 0 53 1 0
#> 46 24.00 0 71 0 0
#> 11.1 24.00 0 42 0 1
#> 126 24.00 0 48 0 0
#> 161 24.00 0 45 0 0
#> 120 24.00 0 68 0 1
#> 191 24.00 0 60 0 1
#> 71 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 112 24.00 0 61 0 0
#> 151.1 24.00 0 42 0 0
#> 54.1 24.00 0 53 1 0
#> 2 24.00 0 9 0 0
#> 2.1 24.00 0 9 0 0
#> 141.1 24.00 0 44 1 0
#> 17.1 24.00 0 38 0 1
#> 162 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 178 24.00 0 52 1 0
#> 38 24.00 0 31 1 0
#> 191.1 24.00 0 60 0 1
#> 115 24.00 0 NA 1 0
#> 44 24.00 0 56 0 0
#> 161.1 24.00 0 45 0 0
#> 104.1 24.00 0 50 1 0
#> 17.2 24.00 0 38 0 1
#> 34.1 24.00 0 36 0 0
#> 174 24.00 0 49 1 0
#> 103.1 24.00 0 56 1 0
#> 151.2 24.00 0 42 0 0
#> 27.1 24.00 0 63 1 0
#> 47 24.00 0 38 0 1
#> 122 24.00 0 66 0 0
#> 3 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 191.2 24.00 0 60 0 1
#> 65 24.00 0 57 1 0
#> 121 24.00 0 57 1 0
#> 20 24.00 0 46 1 0
#> 75 24.00 0 21 1 0
#> 46.1 24.00 0 71 0 0
#> 142 24.00 0 53 0 0
#> 73 24.00 0 NA 0 1
#> 84 24.00 0 39 0 1
#> 152.1 24.00 0 36 0 1
#> 46.2 24.00 0 71 0 0
#> 148 24.00 0 61 1 0
#> 156.1 24.00 0 50 1 0
#> 1 24.00 0 23 1 0
#> 119 24.00 0 17 0 0
#> 20.1 24.00 0 46 1 0
#> 162.1 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 132.1 24.00 0 55 0 0
#> 151.3 24.00 0 42 0 0
#> 28 24.00 0 67 1 0
#> 28.1 24.00 0 67 1 0
#> 82 24.00 0 34 0 0
#> 75.1 24.00 0 21 1 0
#> 54.2 24.00 0 53 1 0
#> 160 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 22.1 24.00 0 52 1 0
#> 135.1 24.00 0 58 1 0
#> 95 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.570 NA NA NA
#> 2 age, Cure model 0.0142 NA NA NA
#> 3 grade_ii, Cure model -0.380 NA NA NA
#> 4 grade_iii, Cure model 0.853 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00267 NA NA NA
#> 2 grade_ii, Survival model 0.719 NA NA NA
#> 3 grade_iii, Survival model 0.401 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.56995 0.01415 -0.38012 0.85340
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.4
#> Residual Deviance: 253.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.5699515 0.0141547 -0.3801204 0.8533958
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0026712 0.7188807 0.4009038
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.156584299 0.484649746 0.564725998 0.624854917 0.132507362 0.808229914
#> [7] 0.082497827 0.971505773 0.698107461 0.949910515 0.069040203 0.260287629
#> [13] 0.381710172 0.039028491 0.992880912 0.502755757 0.590786998 0.899007081
#> [19] 0.607815218 0.410074764 0.381710172 0.681942560 0.341931391 0.008019049
#> [25] 0.690039683 0.555877768 0.899007081 0.899007081 0.792808805 0.590786998
#> [31] 0.120144980 0.410074764 0.529623016 0.884033970 0.529623016 0.624854917
#> [37] 0.410074764 0.214158359 0.260287629 0.721985750 0.322152334 0.745519853
#> [43] 0.706109045 0.341931391 0.582125588 0.311875708 0.475210084 0.249137082
#> [49] 0.899007081 0.949910515 0.978666844 0.853898870 0.831177348 0.869092794
#> [55] 0.891545835 0.928142357 0.082497827 0.657729146 0.361849382 0.054469779
#> [61] 0.168784583 0.721985750 0.226612038 0.761340264 0.322152334 0.745519853
#> [67] 0.721985750 0.769261618 0.815982590 0.657729146 0.168784583 0.978666844
#> [73] 0.831177348 0.714078782 0.935471322 0.861489750 0.484649746 0.024619481
#> [79] 0.649455306 0.624854917 0.465785764 0.456381644 0.831177348 0.168784583
#> [85] 0.784928844 0.371760130 0.381710172 0.260287629 0.792808805 0.616354148
#> [91] 0.529623016 0.511744085 0.769261618 0.168784583 0.964298270 0.673859651
#> [97] 0.935471322 0.226612038 0.410074764 0.107934753 0.815982590 0.511744085
#> [103] 0.132507362 0.301636522 0.446927823 0.869092794 0.564725998 0.291098951
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000
#>
#> $Time
#> 194 41 45 85 169 155 113 25 125 16 69 36 170
#> 22.40 18.02 17.42 16.44 22.41 13.08 22.86 6.32 15.65 8.71 23.23 21.19 19.54
#> 168 127 40 171 61 130 55 170.1 100 150 78 26 111
#> 23.72 3.53 18.00 16.57 10.12 16.47 19.34 19.54 16.07 20.33 23.88 15.77 17.45
#> 61.1 61.2 60 171.1 15 55.1 110 56 110.1 192 58 175 99
#> 10.12 10.12 13.15 16.57 22.68 19.34 17.56 12.21 17.56 16.44 19.34 21.91 21.19
#> 180 128 133 39 150.1 106 68 8 139 61.3 16.1 91 140
#> 14.82 20.35 14.65 15.59 20.33 16.67 20.62 18.43 21.49 10.12 8.71 5.33 12.68
#> 14 37 49 145 113.1 79 158 164 66 180.1 197 96 128.1
#> 12.89 12.52 12.19 10.07 22.86 16.23 20.14 23.60 22.13 14.82 21.60 14.54 20.35
#> 133.1 180.2 13 123 79.1 66.1 91.1 14.1 29 183 177 41.1 86
#> 14.65 14.82 14.34 13.00 16.23 22.13 5.33 12.89 15.45 9.24 12.53 18.02 23.81
#> 5 192.1 179 97 14.2 66.2 81 105 170.2 36.1 60.1 181 110.2
#> 16.43 16.44 18.63 19.14 12.89 22.13 14.06 19.75 19.54 21.19 13.15 16.46 17.56
#> 184 13.1 66.3 77 188 183.1 197.1 55.2 63 123.1 184.1 169.1 190
#> 17.77 14.34 22.13 7.27 16.16 9.24 21.60 19.34 22.77 13.00 17.77 22.41 20.81
#> 76 37.1 45.1 90 151 182 138 118 132 103 22 11 12
#> 19.22 12.52 17.42 20.94 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 156 34 53 9 152 182.1 144 135 7 64 31 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 54 46 11.1 126 161 120 191 71 17 112 151.1 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 2.1 141.1 17.1 162 21 178 38 191.1 44 161.1 104.1 17.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.1 174 103.1 151.2 27.1 47 122 3 143 191.2 65 121 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 46.1 142 84 152.1 46.2 148 156.1 1 119 20.1 162.1 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 151.3 28 28.1 82 75.1 54.2 160 196 22.1 135.1 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[82]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.00781287 0.39477489 0.10955015
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.331154403 0.003909508 -0.041025095
#> grade_iii, Cure model
#> 1.180751377
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 194 22.40 1 38 0 1
#> 171 16.57 1 41 0 1
#> 169 22.41 1 46 0 0
#> 5 16.43 1 51 0 1
#> 192 16.44 1 31 1 0
#> 63 22.77 1 31 1 0
#> 15 22.68 1 48 0 0
#> 92 22.92 1 47 0 1
#> 166 19.98 1 48 0 0
#> 43 12.10 1 61 0 1
#> 113 22.86 1 34 0 0
#> 86 23.81 1 58 0 1
#> 177 12.53 1 75 0 0
#> 106 16.67 1 49 1 0
#> 107 11.18 1 54 1 0
#> 139 21.49 1 63 1 0
#> 150 20.33 1 48 0 0
#> 159 10.55 1 50 0 1
#> 101 9.97 1 10 0 1
#> 188 16.16 1 46 0 1
#> 61 10.12 1 36 0 1
#> 25 6.32 1 34 1 0
#> 77 7.27 1 67 0 1
#> 197 21.60 1 69 1 0
#> 183 9.24 1 67 1 0
#> 155 13.08 1 26 0 0
#> 181 16.46 1 45 0 1
#> 4 17.64 1 NA 0 1
#> 25.1 6.32 1 34 1 0
#> 88 18.37 1 47 0 0
#> 195 11.76 1 NA 1 0
#> 192.1 16.44 1 31 1 0
#> 125 15.65 1 67 1 0
#> 51 18.23 1 83 0 1
#> 93 10.33 1 52 0 1
#> 88.1 18.37 1 47 0 0
#> 39 15.59 1 37 0 1
#> 177.1 12.53 1 75 0 0
#> 45 17.42 1 54 0 1
#> 66 22.13 1 53 0 0
#> 86.1 23.81 1 58 0 1
#> 123 13.00 1 44 1 0
#> 101.1 9.97 1 10 0 1
#> 197.1 21.60 1 69 1 0
#> 14 12.89 1 21 0 0
#> 150.1 20.33 1 48 0 0
#> 113.1 22.86 1 34 0 0
#> 158 20.14 1 74 1 0
#> 18 15.21 1 49 1 0
#> 23 16.92 1 61 0 0
#> 60 13.15 1 38 1 0
#> 169.1 22.41 1 46 0 0
#> 199 19.81 1 NA 0 1
#> 150.2 20.33 1 48 0 0
#> 166.1 19.98 1 48 0 0
#> 194.1 22.40 1 38 0 1
#> 43.1 12.10 1 61 0 1
#> 77.1 7.27 1 67 0 1
#> 25.2 6.32 1 34 1 0
#> 77.2 7.27 1 67 0 1
#> 136 21.83 1 43 0 1
#> 169.2 22.41 1 46 0 0
#> 43.2 12.10 1 61 0 1
#> 69 23.23 1 25 0 1
#> 5.1 16.43 1 51 0 1
#> 79 16.23 1 54 1 0
#> 68 20.62 1 44 0 0
#> 41 18.02 1 40 1 0
#> 16 8.71 1 71 0 1
#> 91 5.33 1 61 0 1
#> 133 14.65 1 57 0 0
#> 50 10.02 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 10 10.53 1 34 0 0
#> 55 19.34 1 69 0 1
#> 90 20.94 1 50 0 1
#> 23.1 16.92 1 61 0 0
#> 25.3 6.32 1 34 1 0
#> 10.1 10.53 1 34 0 0
#> 86.2 23.81 1 58 0 1
#> 63.1 22.77 1 31 1 0
#> 40 18.00 1 28 1 0
#> 29 15.45 1 68 1 0
#> 127 3.53 1 62 0 1
#> 194.2 22.40 1 38 0 1
#> 190 20.81 1 42 1 0
#> 136.1 21.83 1 43 0 1
#> 16.1 8.71 1 71 0 1
#> 130 16.47 1 53 0 1
#> 117 17.46 1 26 0 1
#> 63.2 22.77 1 31 1 0
#> 69.1 23.23 1 25 0 1
#> 96 14.54 1 33 0 1
#> 108 18.29 1 39 0 1
#> 86.3 23.81 1 58 0 1
#> 177.2 12.53 1 75 0 0
#> 24 23.89 1 38 0 0
#> 91.1 5.33 1 61 0 1
#> 155.1 13.08 1 26 0 0
#> 26 15.77 1 49 0 1
#> 76 19.22 1 54 0 1
#> 128 20.35 1 35 0 1
#> 6 15.64 1 39 0 0
#> 123.1 13.00 1 44 1 0
#> 166.2 19.98 1 48 0 0
#> 13 14.34 1 54 0 1
#> 149 8.37 1 33 1 0
#> 199.1 19.81 1 NA 0 1
#> 76.1 19.22 1 54 0 1
#> 190.1 20.81 1 42 1 0
#> 25.4 6.32 1 34 1 0
#> 57 14.46 1 45 0 1
#> 161 24.00 0 45 0 0
#> 94 24.00 0 51 0 1
#> 82 24.00 0 34 0 0
#> 94.1 24.00 0 51 0 1
#> 71 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 178 24.00 0 52 1 0
#> 186 24.00 0 45 1 0
#> 28 24.00 0 67 1 0
#> 115 24.00 0 NA 1 0
#> 44 24.00 0 56 0 0
#> 186.1 24.00 0 45 1 0
#> 160 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 112 24.00 0 61 0 0
#> 102 24.00 0 49 0 0
#> 35 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 102.1 24.00 0 49 0 0
#> 75 24.00 0 21 1 0
#> 11 24.00 0 42 0 1
#> 3 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 178.1 24.00 0 52 1 0
#> 20 24.00 0 46 1 0
#> 200 24.00 0 64 0 0
#> 103 24.00 0 56 1 0
#> 47 24.00 0 38 0 1
#> 72 24.00 0 40 0 1
#> 185 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 102.2 24.00 0 49 0 0
#> 98 24.00 0 34 1 0
#> 174 24.00 0 49 1 0
#> 65 24.00 0 57 1 0
#> 67 24.00 0 25 0 0
#> 156 24.00 0 50 1 0
#> 147 24.00 0 76 1 0
#> 67.1 24.00 0 25 0 0
#> 21 24.00 0 47 0 0
#> 65.1 24.00 0 57 1 0
#> 137 24.00 0 45 1 0
#> 141 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 67.2 24.00 0 25 0 0
#> 84 24.00 0 39 0 1
#> 160.1 24.00 0 31 1 0
#> 103.1 24.00 0 56 1 0
#> 94.2 24.00 0 51 0 1
#> 20.1 24.00 0 46 1 0
#> 64 24.00 0 43 0 0
#> 3.1 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 147.1 24.00 0 76 1 0
#> 94.3 24.00 0 51 0 1
#> 47.1 24.00 0 38 0 1
#> 87 24.00 0 27 0 0
#> 62 24.00 0 71 0 0
#> 118.1 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 152 24.00 0 36 0 1
#> 34 24.00 0 36 0 0
#> 102.3 24.00 0 49 0 0
#> 146 24.00 0 63 1 0
#> 148 24.00 0 61 1 0
#> 172 24.00 0 41 0 0
#> 151.1 24.00 0 42 0 0
#> 147.2 24.00 0 76 1 0
#> 193 24.00 0 45 0 1
#> 27 24.00 0 63 1 0
#> 83 24.00 0 6 0 0
#> 72.1 24.00 0 40 0 1
#> 67.3 24.00 0 25 0 0
#> 118.2 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 11.1 24.00 0 42 0 1
#> 174.1 24.00 0 49 1 0
#> 71.1 24.00 0 51 0 0
#> 137.1 24.00 0 45 1 0
#> 165.1 24.00 0 47 0 0
#> 142.1 24.00 0 53 0 0
#> 67.4 24.00 0 25 0 0
#> 34.1 24.00 0 36 0 0
#> 72.2 24.00 0 40 0 1
#> 62.1 24.00 0 71 0 0
#> 17 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.331 NA NA NA
#> 2 age, Cure model 0.00391 NA NA NA
#> 3 grade_ii, Cure model -0.0410 NA NA NA
#> 4 grade_iii, Cure model 1.18 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00781 NA NA NA
#> 2 grade_ii, Survival model 0.395 NA NA NA
#> 3 grade_iii, Survival model 0.110 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.33115 0.00391 -0.04103 1.18075
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 252.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.331154403 0.003909508 -0.041025095 1.180751377
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.00781287 0.39477489 0.10955015
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.34032512 0.66468364 0.30418725 0.70091459 0.68668809 0.25214507
#> [7] 0.29092164 0.20448317 0.52123395 0.85147278 0.22124743 0.10584011
#> [13] 0.83314913 0.65725215 0.86948747 0.42885223 0.48592880 0.87548168
#> [19] 0.90510987 0.72191943 0.89921206 0.95666225 0.93986333 0.40841165
#> [25] 0.91683561 0.80167833 0.67940247 0.95666225 0.57130859 0.68668809
#> [31] 0.73573168 0.59558033 0.89329569 0.57130859 0.74928902 0.83314913
#> [37] 0.63463301 0.37464065 0.10584011 0.81438841 0.90510987 0.40841165
#> [43] 0.82688534 0.48592880 0.22124743 0.51247953 0.76267438 0.64227513
#> [49] 0.79527495 0.30418725 0.48592880 0.52123395 0.34032512 0.85147278
#> [55] 0.93986333 0.95666225 0.93986333 0.38625954 0.30418725 0.85147278
#> [61] 0.17071287 0.70091459 0.71495249 0.46734290 0.60354747 0.92266111
#> [67] 0.98375876 0.76925444 0.61918364 0.88144936 0.54648958 0.43885288
#> [73] 0.64227513 0.95666225 0.88144936 0.10584011 0.25214507 0.61140789
#> [79] 0.75602686 0.99459233 0.34032512 0.44870778 0.38625954 0.92266111
#> [85] 0.67207078 0.62692580 0.25214507 0.17071287 0.77580308 0.58749047
#> [91] 0.10584011 0.83314913 0.05034016 0.98375876 0.80167833 0.72884637
#> [97] 0.55492081 0.47667812 0.74252137 0.81438841 0.52123395 0.78881974
#> [103] 0.93413908 0.55492081 0.44870778 0.95666225 0.78232727 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000
#>
#> $Time
#> 194 171 169 5 192 63 15 92 166 43 113 86 177
#> 22.40 16.57 22.41 16.43 16.44 22.77 22.68 22.92 19.98 12.10 22.86 23.81 12.53
#> 106 107 139 150 159 101 188 61 25 77 197 183 155
#> 16.67 11.18 21.49 20.33 10.55 9.97 16.16 10.12 6.32 7.27 21.60 9.24 13.08
#> 181 25.1 88 192.1 125 51 93 88.1 39 177.1 45 66 86.1
#> 16.46 6.32 18.37 16.44 15.65 18.23 10.33 18.37 15.59 12.53 17.42 22.13 23.81
#> 123 101.1 197.1 14 150.1 113.1 158 18 23 60 169.1 150.2 166.1
#> 13.00 9.97 21.60 12.89 20.33 22.86 20.14 15.21 16.92 13.15 22.41 20.33 19.98
#> 194.1 43.1 77.1 25.2 77.2 136 169.2 43.2 69 5.1 79 68 41
#> 22.40 12.10 7.27 6.32 7.27 21.83 22.41 12.10 23.23 16.43 16.23 20.62 18.02
#> 16 91 133 184 10 55 90 23.1 25.3 10.1 86.2 63.1 40
#> 8.71 5.33 14.65 17.77 10.53 19.34 20.94 16.92 6.32 10.53 23.81 22.77 18.00
#> 29 127 194.2 190 136.1 16.1 130 117 63.2 69.1 96 108 86.3
#> 15.45 3.53 22.40 20.81 21.83 8.71 16.47 17.46 22.77 23.23 14.54 18.29 23.81
#> 177.2 24 91.1 155.1 26 76 128 6 123.1 166.2 13 149 76.1
#> 12.53 23.89 5.33 13.08 15.77 19.22 20.35 15.64 13.00 19.98 14.34 8.37 19.22
#> 190.1 25.4 57 161 94 82 94.1 71 142 178 186 28 44
#> 20.81 6.32 14.46 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.1 160 143 112 102 35 151 102.1 75 11 3 48 178.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 200 103 47 72 185 118 163 165 102.2 98 174 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 156 147 67.1 21 65.1 137 141 95 67.2 84 160.1 103.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.2 20.1 64 3.1 120 147.1 94.3 47.1 87 62 118.1 182 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 102.3 146 148 172 151.1 147.2 193 27 83 72.1 67.3 118.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 11.1 174.1 71.1 137.1 165.1 142.1 67.4 34.1 72.2 62.1 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[83]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003670069 0.904677417 0.261879183
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.9570452 0.0261401 -0.6832846
#> grade_iii, Cure model
#> 0.5666594
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 177 12.53 1 75 0 0
#> 90 20.94 1 50 0 1
#> 60 13.15 1 38 1 0
#> 5 16.43 1 51 0 1
#> 195 11.76 1 NA 1 0
#> 189 10.51 1 NA 1 0
#> 134 17.81 1 47 1 0
#> 69 23.23 1 25 0 1
#> 51 18.23 1 83 0 1
#> 149 8.37 1 33 1 0
#> 26 15.77 1 49 0 1
#> 6 15.64 1 39 0 0
#> 117 17.46 1 26 0 1
#> 127 3.53 1 62 0 1
#> 77 7.27 1 67 0 1
#> 29 15.45 1 68 1 0
#> 14 12.89 1 21 0 0
#> 133 14.65 1 57 0 0
#> 42 12.43 1 49 0 1
#> 66 22.13 1 53 0 0
#> 14.1 12.89 1 21 0 0
#> 192 16.44 1 31 1 0
#> 13 14.34 1 54 0 1
#> 195.1 11.76 1 NA 1 0
#> 13.1 14.34 1 54 0 1
#> 183 9.24 1 67 1 0
#> 58 19.34 1 39 0 0
#> 36 21.19 1 48 0 1
#> 37 12.52 1 57 1 0
#> 49 12.19 1 48 1 0
#> 5.1 16.43 1 51 0 1
#> 6.1 15.64 1 39 0 0
#> 5.2 16.43 1 51 0 1
#> 133.1 14.65 1 57 0 0
#> 180 14.82 1 37 0 0
#> 57 14.46 1 45 0 1
#> 177.1 12.53 1 75 0 0
#> 36.1 21.19 1 48 0 1
#> 78 23.88 1 43 0 0
#> 105 19.75 1 60 0 0
#> 110 17.56 1 65 0 1
#> 175 21.91 1 43 0 0
#> 157 15.10 1 47 0 0
#> 123 13.00 1 44 1 0
#> 158 20.14 1 74 1 0
#> 57.1 14.46 1 45 0 1
#> 145 10.07 1 65 1 0
#> 88 18.37 1 47 0 0
#> 92 22.92 1 47 0 1
#> 14.2 12.89 1 21 0 0
#> 184 17.77 1 38 0 0
#> 139 21.49 1 63 1 0
#> 127.1 3.53 1 62 0 1
#> 15 22.68 1 48 0 0
#> 68 20.62 1 44 0 0
#> 124 9.73 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 194 22.40 1 38 0 1
#> 134.1 17.81 1 47 1 0
#> 85 16.44 1 36 0 0
#> 139.1 21.49 1 63 1 0
#> 52 10.42 1 52 0 1
#> 37.1 12.52 1 57 1 0
#> 169 22.41 1 46 0 0
#> 36.2 21.19 1 48 0 1
#> 56 12.21 1 60 0 0
#> 184.1 17.77 1 38 0 0
#> 13.2 14.34 1 54 0 1
#> 78.1 23.88 1 43 0 0
#> 180.1 14.82 1 37 0 0
#> 124.1 9.73 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 113 22.86 1 34 0 0
#> 25 6.32 1 34 1 0
#> 187 9.92 1 39 1 0
#> 184.2 17.77 1 38 0 0
#> 107 11.18 1 54 1 0
#> 57.2 14.46 1 45 0 1
#> 130 16.47 1 53 0 1
#> 145.1 10.07 1 65 1 0
#> 164 23.60 1 76 0 1
#> 140 12.68 1 59 1 0
#> 55 19.34 1 69 0 1
#> 6.2 15.64 1 39 0 0
#> 61 10.12 1 36 0 1
#> 61.1 10.12 1 36 0 1
#> 155 13.08 1 26 0 0
#> 37.2 12.52 1 57 1 0
#> 114 13.68 1 NA 0 0
#> 50 10.02 1 NA 1 0
#> 59 10.16 1 NA 1 0
#> 52.1 10.42 1 52 0 1
#> 140.1 12.68 1 59 1 0
#> 77.1 7.27 1 67 0 1
#> 5.3 16.43 1 51 0 1
#> 114.1 13.68 1 NA 0 0
#> 183.1 9.24 1 67 1 0
#> 26.1 15.77 1 49 0 1
#> 149.1 8.37 1 33 1 0
#> 93 10.33 1 52 0 1
#> 40 18.00 1 28 1 0
#> 123.1 13.00 1 44 1 0
#> 192.1 16.44 1 31 1 0
#> 91 5.33 1 61 0 1
#> 180.2 14.82 1 37 0 0
#> 140.2 12.68 1 59 1 0
#> 167 15.55 1 56 1 0
#> 110.1 17.56 1 65 0 1
#> 66.1 22.13 1 53 0 0
#> 85.1 16.44 1 36 0 0
#> 164.1 23.60 1 76 0 1
#> 88.1 18.37 1 47 0 0
#> 33 24.00 0 53 0 0
#> 17 24.00 0 38 0 1
#> 2 24.00 0 9 0 0
#> 186 24.00 0 45 1 0
#> 143 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 148 24.00 0 61 1 0
#> 160 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 103 24.00 0 56 1 0
#> 31 24.00 0 36 0 1
#> 160.1 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 82 24.00 0 34 0 0
#> 109 24.00 0 48 0 0
#> 118 24.00 0 44 1 0
#> 186.1 24.00 0 45 1 0
#> 28 24.00 0 67 1 0
#> 161 24.00 0 45 0 0
#> 116 24.00 0 58 0 1
#> 67 24.00 0 25 0 0
#> 82.1 24.00 0 34 0 0
#> 9.1 24.00 0 31 1 0
#> 34.1 24.00 0 36 0 0
#> 1 24.00 0 23 1 0
#> 118.1 24.00 0 44 1 0
#> 141 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 65 24.00 0 57 1 0
#> 116.1 24.00 0 58 0 1
#> 74 24.00 0 43 0 1
#> 144 24.00 0 28 0 1
#> 3 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 152 24.00 0 36 0 1
#> 64 24.00 0 43 0 0
#> 3.1 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 198 24.00 0 66 0 1
#> 112 24.00 0 61 0 0
#> 62 24.00 0 71 0 0
#> 185 24.00 0 44 1 0
#> 64.1 24.00 0 43 0 0
#> 118.2 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 75 24.00 0 21 1 0
#> 116.2 24.00 0 58 0 1
#> 28.1 24.00 0 67 1 0
#> 65.1 24.00 0 57 1 0
#> 151.1 24.00 0 42 0 0
#> 147 24.00 0 76 1 0
#> 142 24.00 0 53 0 0
#> 121 24.00 0 57 1 0
#> 28.2 24.00 0 67 1 0
#> 146 24.00 0 63 1 0
#> 156 24.00 0 50 1 0
#> 165 24.00 0 47 0 0
#> 84 24.00 0 39 0 1
#> 17.1 24.00 0 38 0 1
#> 46 24.00 0 71 0 0
#> 119 24.00 0 17 0 0
#> 67.1 24.00 0 25 0 0
#> 11 24.00 0 42 0 1
#> 3.2 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 174 24.00 0 49 1 0
#> 178 24.00 0 52 1 0
#> 118.3 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 2.1 24.00 0 9 0 0
#> 144.1 24.00 0 28 0 1
#> 118.4 24.00 0 44 1 0
#> 54 24.00 0 53 1 0
#> 73 24.00 0 NA 0 1
#> 196 24.00 0 19 0 0
#> 118.5 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 144.2 24.00 0 28 0 1
#> 138 24.00 0 44 1 0
#> 82.2 24.00 0 34 0 0
#> 174.1 24.00 0 49 1 0
#> 178.1 24.00 0 52 1 0
#> 147.1 24.00 0 76 1 0
#> 87 24.00 0 27 0 0
#> 142.1 24.00 0 53 0 0
#> 146.1 24.00 0 63 1 0
#> 165.1 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.957 NA NA NA
#> 2 age, Cure model 0.0261 NA NA NA
#> 3 grade_ii, Cure model -0.683 NA NA NA
#> 4 grade_iii, Cure model 0.567 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00367 NA NA NA
#> 2 grade_ii, Survival model 0.905 NA NA NA
#> 3 grade_iii, Survival model 0.262 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.95705 0.02614 -0.68328 0.56666
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 245.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.9570452 0.0261401 -0.6832846 0.5666594
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003670069 0.904677417 0.261879183
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.783275538 0.236123297 0.695324497 0.482513669 0.345815706 0.054331362
#> [7] 0.323977008 0.939051339 0.519502934 0.538280910 0.415083735 0.984857578
#> [13] 0.954350648 0.575766972 0.731291836 0.621752079 0.825379946 0.129861165
#> [19] 0.731291836 0.445304668 0.667862178 0.667862178 0.923449748 0.280501111
#> [25] 0.203904992 0.800493939 0.842142326 0.482513669 0.538280910 0.482513669
#> [31] 0.621752079 0.594254892 0.640325561 0.783275538 0.203904992 0.009774927
#> [37] 0.269531789 0.395146300 0.155015403 0.584999359 0.713609714 0.258650046
#> [43] 0.640325561 0.899480898 0.302114874 0.066744830 0.731291836 0.365586196
#> [49] 0.181498848 0.984857578 0.091390520 0.247348393 0.168313953 0.117076864
#> [55] 0.345815706 0.445304668 0.181498848 0.858661692 0.800493939 0.104109793
#> [61] 0.203904992 0.833752810 0.365586196 0.667862178 0.009774927 0.594254892
#> [67] 0.425130897 0.078953135 0.969646012 0.915489797 0.365586196 0.850443195
#> [73] 0.640325561 0.435225922 0.899480898 0.031524587 0.757724815 0.280501111
#> [79] 0.538280910 0.883197660 0.883197660 0.704461705 0.800493939 0.858661692
#> [85] 0.757724815 0.954350648 0.482513669 0.923449748 0.519502934 0.939051339
#> [91] 0.874997124 0.335115014 0.713609714 0.445304668 0.977252941 0.594254892
#> [97] 0.757724815 0.566395536 0.395146300 0.129861165 0.445304668 0.031524587
#> [103] 0.302114874 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 177 90 60 5 134 69 51 149 26 6 117 127 77
#> 12.53 20.94 13.15 16.43 17.81 23.23 18.23 8.37 15.77 15.64 17.46 3.53 7.27
#> 29 14 133 42 66 14.1 192 13 13.1 183 58 36 37
#> 15.45 12.89 14.65 12.43 22.13 12.89 16.44 14.34 14.34 9.24 19.34 21.19 12.52
#> 49 5.1 6.1 5.2 133.1 180 57 177.1 36.1 78 105 110 175
#> 12.19 16.43 15.64 16.43 14.65 14.82 14.46 12.53 21.19 23.88 19.75 17.56 21.91
#> 157 123 158 57.1 145 88 92 14.2 184 139 127.1 15 68
#> 15.10 13.00 20.14 14.46 10.07 18.37 22.92 12.89 17.77 21.49 3.53 22.68 20.62
#> 136 194 134.1 85 139.1 52 37.1 169 36.2 56 184.1 13.2 78.1
#> 21.83 22.40 17.81 16.44 21.49 10.42 12.52 22.41 21.19 12.21 17.77 14.34 23.88
#> 180.1 23 113 25 187 184.2 107 57.2 130 145.1 164 140 55
#> 14.82 16.92 22.86 6.32 9.92 17.77 11.18 14.46 16.47 10.07 23.60 12.68 19.34
#> 6.2 61 61.1 155 37.2 52.1 140.1 77.1 5.3 183.1 26.1 149.1 93
#> 15.64 10.12 10.12 13.08 12.52 10.42 12.68 7.27 16.43 9.24 15.77 8.37 10.33
#> 40 123.1 192.1 91 180.2 140.2 167 110.1 66.1 85.1 164.1 88.1 33
#> 18.00 13.00 16.44 5.33 14.82 12.68 15.55 17.56 22.13 16.44 23.60 18.37 24.00
#> 17 2 186 143 47 148 160 34 103 31 160.1 9 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 109 118 186.1 28 161 116 67 82.1 9.1 34.1 1 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 98 65 116.1 74 144 3 19 152 64 3.1 151 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 62 185 64.1 118.2 137 75 116.2 28.1 65.1 151.1 147 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 28.2 146 156 165 84 17.1 46 119 67.1 11 3.2 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 178 118.3 35 2.1 144.1 118.4 54 196 118.5 22 144.2 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.2 174.1 178.1 147.1 87 142.1 146.1 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[84]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00303838 0.72742471 0.42026624
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.16016944 0.01828237 -0.22006226
#> grade_iii, Cure model
#> 1.36739635
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 30 17.43 1 78 0 0
#> 99 21.19 1 38 0 1
#> 57 14.46 1 45 0 1
#> 70 7.38 1 30 1 0
#> 70.1 7.38 1 30 1 0
#> 159 10.55 1 50 0 1
#> 51 18.23 1 83 0 1
#> 78 23.88 1 43 0 0
#> 40 18.00 1 28 1 0
#> 188 16.16 1 46 0 1
#> 13 14.34 1 54 0 1
#> 145 10.07 1 65 1 0
#> 63 22.77 1 31 1 0
#> 171 16.57 1 41 0 1
#> 194 22.40 1 38 0 1
#> 91 5.33 1 61 0 1
#> 13.1 14.34 1 54 0 1
#> 86 23.81 1 58 0 1
#> 150 20.33 1 48 0 0
#> 128 20.35 1 35 0 1
#> 40.1 18.00 1 28 1 0
#> 183 9.24 1 67 1 0
#> 49 12.19 1 48 1 0
#> 105 19.75 1 60 0 0
#> 125 15.65 1 67 1 0
#> 164 23.60 1 76 0 1
#> 90 20.94 1 50 0 1
#> 15 22.68 1 48 0 0
#> 100 16.07 1 60 0 0
#> 93 10.33 1 52 0 1
#> 180 14.82 1 37 0 0
#> 32 20.90 1 37 1 0
#> 180.1 14.82 1 37 0 0
#> 16 8.71 1 71 0 1
#> 91.1 5.33 1 61 0 1
#> 51.1 18.23 1 83 0 1
#> 15.1 22.68 1 48 0 0
#> 23 16.92 1 61 0 0
#> 79 16.23 1 54 1 0
#> 157 15.10 1 47 0 0
#> 179 18.63 1 42 0 0
#> 111 17.45 1 47 0 1
#> 78.1 23.88 1 43 0 0
#> 14 12.89 1 21 0 0
#> 127 3.53 1 62 0 1
#> 155 13.08 1 26 0 0
#> 24 23.89 1 38 0 0
#> 92 22.92 1 47 0 1
#> 199 19.81 1 NA 0 1
#> 56 12.21 1 60 0 0
#> 164.1 23.60 1 76 0 1
#> 124 9.73 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 197 21.60 1 69 1 0
#> 190 20.81 1 42 1 0
#> 111.1 17.45 1 47 0 1
#> 139 21.49 1 63 1 0
#> 93.1 10.33 1 52 0 1
#> 45 17.42 1 54 0 1
#> 164.2 23.60 1 76 0 1
#> 136 21.83 1 43 0 1
#> 86.1 23.81 1 58 0 1
#> 130 16.47 1 53 0 1
#> 60 13.15 1 38 1 0
#> 139.1 21.49 1 63 1 0
#> 26 15.77 1 49 0 1
#> 90.1 20.94 1 50 0 1
#> 91.2 5.33 1 61 0 1
#> 111.2 17.45 1 47 0 1
#> 6 15.64 1 39 0 0
#> 43 12.10 1 61 0 1
#> 114 13.68 1 NA 0 0
#> 90.2 20.94 1 50 0 1
#> 88 18.37 1 47 0 0
#> 45.1 17.42 1 54 0 1
#> 117 17.46 1 26 0 1
#> 8 18.43 1 32 0 0
#> 125.1 15.65 1 67 1 0
#> 57.1 14.46 1 45 0 1
#> 123 13.00 1 44 1 0
#> 179.1 18.63 1 42 0 0
#> 171.1 16.57 1 41 0 1
#> 30.1 17.43 1 78 0 0
#> 24.1 23.89 1 38 0 0
#> 117.1 17.46 1 26 0 1
#> 85 16.44 1 36 0 0
#> 199.1 19.81 1 NA 0 1
#> 101 9.97 1 10 0 1
#> 110 17.56 1 65 0 1
#> 188.1 16.16 1 46 0 1
#> 13.2 14.34 1 54 0 1
#> 50 10.02 1 NA 1 0
#> 91.3 5.33 1 61 0 1
#> 181 16.46 1 45 0 1
#> 90.3 20.94 1 50 0 1
#> 114.1 13.68 1 NA 0 0
#> 68 20.62 1 44 0 0
#> 136.1 21.83 1 43 0 1
#> 42 12.43 1 49 0 1
#> 145.1 10.07 1 65 1 0
#> 89 11.44 1 NA 0 0
#> 55 19.34 1 69 0 1
#> 39 15.59 1 37 0 1
#> 171.2 16.57 1 41 0 1
#> 199.2 19.81 1 NA 0 1
#> 99.1 21.19 1 38 0 1
#> 16.1 8.71 1 71 0 1
#> 140 12.68 1 59 1 0
#> 188.2 16.16 1 46 0 1
#> 183.1 9.24 1 67 1 0
#> 164.3 23.60 1 76 0 1
#> 90.4 20.94 1 50 0 1
#> 102 24.00 0 49 0 0
#> 65 24.00 0 57 1 0
#> 121 24.00 0 57 1 0
#> 47 24.00 0 38 0 1
#> 185 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 131 24.00 0 66 0 0
#> 173 24.00 0 19 0 1
#> 11 24.00 0 42 0 1
#> 178 24.00 0 52 1 0
#> 9 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 148 24.00 0 61 1 0
#> 17 24.00 0 38 0 1
#> 151 24.00 0 42 0 0
#> 163 24.00 0 66 0 0
#> 141 24.00 0 44 1 0
#> 47.1 24.00 0 38 0 1
#> 118 24.00 0 44 1 0
#> 141.1 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 75 24.00 0 21 1 0
#> 71 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 186 24.00 0 45 1 0
#> 118.1 24.00 0 44 1 0
#> 7.1 24.00 0 37 1 0
#> 72 24.00 0 40 0 1
#> 31 24.00 0 36 0 1
#> 109 24.00 0 48 0 0
#> 17.1 24.00 0 38 0 1
#> 31.1 24.00 0 36 0 1
#> 84 24.00 0 39 0 1
#> 47.2 24.00 0 38 0 1
#> 151.1 24.00 0 42 0 0
#> 65.1 24.00 0 57 1 0
#> 172 24.00 0 41 0 0
#> 141.2 24.00 0 44 1 0
#> 172.1 24.00 0 41 0 0
#> 94 24.00 0 51 0 1
#> 1 24.00 0 23 1 0
#> 118.2 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 2 24.00 0 9 0 0
#> 137 24.00 0 45 1 0
#> 122 24.00 0 66 0 0
#> 156 24.00 0 50 1 0
#> 20 24.00 0 46 1 0
#> 172.2 24.00 0 41 0 0
#> 186.1 24.00 0 45 1 0
#> 165 24.00 0 47 0 0
#> 28 24.00 0 67 1 0
#> 142 24.00 0 53 0 0
#> 65.2 24.00 0 57 1 0
#> 112.1 24.00 0 61 0 0
#> 161 24.00 0 45 0 0
#> 193 24.00 0 45 0 1
#> 9.1 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 48 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 20.1 24.00 0 46 1 0
#> 116 24.00 0 58 0 1
#> 65.3 24.00 0 57 1 0
#> 141.3 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 62 24.00 0 71 0 0
#> 131.1 24.00 0 66 0 0
#> 12 24.00 0 63 0 0
#> 162 24.00 0 51 0 0
#> 46 24.00 0 71 0 0
#> 27 24.00 0 63 1 0
#> 132.1 24.00 0 55 0 0
#> 20.2 24.00 0 46 1 0
#> 54 24.00 0 53 1 0
#> 11.1 24.00 0 42 0 1
#> 21 24.00 0 47 0 0
#> 83 24.00 0 6 0 0
#> 131.2 24.00 0 66 0 0
#> 137.1 24.00 0 45 1 0
#> 144 24.00 0 28 0 1
#> 72.1 24.00 0 40 0 1
#> 126 24.00 0 48 0 0
#> 95.1 24.00 0 68 0 1
#> 109.1 24.00 0 48 0 0
#> 71.1 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 141.4 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.16 NA NA NA
#> 2 age, Cure model 0.0183 NA NA NA
#> 3 grade_ii, Cure model -0.220 NA NA NA
#> 4 grade_iii, Cure model 1.37 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00304 NA NA NA
#> 2 grade_ii, Survival model 0.727 NA NA NA
#> 3 grade_iii, Survival model 0.420 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.16017 0.01828 -0.22006 1.36740
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 239.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.16016944 0.01828237 -0.22006226 1.36739635
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00303838 0.72742471 0.42026624
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.54685004 0.28144493 0.75958667 0.94850464 0.94850464 0.87187154
#> [7] 0.45596695 0.04542927 0.47497075 0.66011177 0.77593149 0.89526748
#> [13] 0.17379733 0.60005153 0.21162456 0.96336473 0.77593149 0.07996694
#> [19] 0.38877898 0.37921478 0.47497075 0.91830906 0.85610969 0.39837523
#> [25] 0.70190499 0.11105590 0.30252280 0.18654563 0.68506242 0.87972114
#> [31] 0.74312574 0.35009966 0.74312574 0.93343456 0.96336473 0.45596695
#> [37] 0.18654563 0.58232002 0.65158216 0.73486875 0.41759207 0.52052402
#> [43] 0.04542927 0.82425109 0.99261863 0.80816600 0.01478730 0.16016637
#> [49] 0.84816145 0.11105590 0.59123784 0.24801686 0.35993829 0.52052402
#> [55] 0.25979018 0.87972114 0.56466632 0.11105590 0.22428390 0.07996694
#> [61] 0.62572282 0.80009746 0.25979018 0.69349964 0.30252280 0.96336473
#> [67] 0.52052402 0.71834557 0.86400013 0.30252280 0.44628938 0.56466632
#> [73] 0.50252864 0.43663967 0.70190499 0.75958667 0.81624067 0.41759207
#> [79] 0.60005153 0.54685004 0.01478730 0.50252864 0.64296722 0.91062744
#> [85] 0.49331353 0.66011177 0.77593149 0.96336473 0.63436423 0.30252280
#> [91] 0.36956080 0.22428390 0.84022561 0.89526748 0.40801017 0.72662409
#> [97] 0.60005153 0.28144493 0.93343456 0.83226633 0.66011177 0.91830906
#> [103] 0.11105590 0.30252280 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 30 99 57 70 70.1 159 51 78 40 188 13 145 63
#> 17.43 21.19 14.46 7.38 7.38 10.55 18.23 23.88 18.00 16.16 14.34 10.07 22.77
#> 171 194 91 13.1 86 150 128 40.1 183 49 105 125 164
#> 16.57 22.40 5.33 14.34 23.81 20.33 20.35 18.00 9.24 12.19 19.75 15.65 23.60
#> 90 15 100 93 180 32 180.1 16 91.1 51.1 15.1 23 79
#> 20.94 22.68 16.07 10.33 14.82 20.90 14.82 8.71 5.33 18.23 22.68 16.92 16.23
#> 157 179 111 78.1 14 127 155 24 92 56 164.1 106 197
#> 15.10 18.63 17.45 23.88 12.89 3.53 13.08 23.89 22.92 12.21 23.60 16.67 21.60
#> 190 111.1 139 93.1 45 164.2 136 86.1 130 60 139.1 26 90.1
#> 20.81 17.45 21.49 10.33 17.42 23.60 21.83 23.81 16.47 13.15 21.49 15.77 20.94
#> 91.2 111.2 6 43 90.2 88 45.1 117 8 125.1 57.1 123 179.1
#> 5.33 17.45 15.64 12.10 20.94 18.37 17.42 17.46 18.43 15.65 14.46 13.00 18.63
#> 171.1 30.1 24.1 117.1 85 101 110 188.1 13.2 91.3 181 90.3 68
#> 16.57 17.43 23.89 17.46 16.44 9.97 17.56 16.16 14.34 5.33 16.46 20.94 20.62
#> 136.1 42 145.1 55 39 171.2 99.1 16.1 140 188.2 183.1 164.3 90.4
#> 21.83 12.43 10.07 19.34 15.59 16.57 21.19 8.71 12.68 16.16 9.24 23.60 20.94
#> 102 65 121 47 185 182 131 173 11 178 9 7 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 151 163 141 47.1 118 141.1 112 75 71 67 186 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.1 72 31 109 17.1 31.1 84 47.2 151.1 65.1 172 141.2 172.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 1 118.2 64 2 137 122 156 20 172.2 186.1 165 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 65.2 112.1 161 193 9.1 147 48 95 20.1 116 65.3 141.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 62 131.1 12 162 46 27 132.1 20.2 54 11.1 21 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.2 137.1 144 72.1 126 95.1 109.1 71.1 22 141.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[85]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003504025 0.161607320 0.160286119
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.44452706 0.01703031 0.81802622
#> grade_iii, Cure model
#> 1.57530277
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 145 10.07 1 65 1 0
#> 170 19.54 1 43 0 1
#> 140 12.68 1 59 1 0
#> 26 15.77 1 49 0 1
#> 188 16.16 1 46 0 1
#> 183 9.24 1 67 1 0
#> 177 12.53 1 75 0 0
#> 92 22.92 1 47 0 1
#> 85 16.44 1 36 0 0
#> 63 22.77 1 31 1 0
#> 63.1 22.77 1 31 1 0
#> 63.2 22.77 1 31 1 0
#> 55 19.34 1 69 0 1
#> 139 21.49 1 63 1 0
#> 189 10.51 1 NA 1 0
#> 32 20.90 1 37 1 0
#> 86 23.81 1 58 0 1
#> 37 12.52 1 57 1 0
#> 68 20.62 1 44 0 0
#> 55.1 19.34 1 69 0 1
#> 127 3.53 1 62 0 1
#> 23 16.92 1 61 0 0
#> 57 14.46 1 45 0 1
#> 149 8.37 1 33 1 0
#> 89 11.44 1 NA 0 0
#> 166 19.98 1 48 0 0
#> 114 13.68 1 NA 0 0
#> 139.1 21.49 1 63 1 0
#> 90 20.94 1 50 0 1
#> 52 10.42 1 52 0 1
#> 181 16.46 1 45 0 1
#> 150 20.33 1 48 0 0
#> 14 12.89 1 21 0 0
#> 49 12.19 1 48 1 0
#> 164 23.60 1 76 0 1
#> 8 18.43 1 32 0 0
#> 175 21.91 1 43 0 0
#> 139.2 21.49 1 63 1 0
#> 117 17.46 1 26 0 1
#> 61 10.12 1 36 0 1
#> 187 9.92 1 39 1 0
#> 179 18.63 1 42 0 0
#> 90.1 20.94 1 50 0 1
#> 18 15.21 1 49 1 0
#> 91 5.33 1 61 0 1
#> 127.1 3.53 1 62 0 1
#> 41 18.02 1 40 1 0
#> 114.1 13.68 1 NA 0 0
#> 153 21.33 1 55 1 0
#> 4 17.64 1 NA 0 1
#> 43 12.10 1 61 0 1
#> 170.1 19.54 1 43 0 1
#> 59 10.16 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 96 14.54 1 33 0 1
#> 107 11.18 1 54 1 0
#> 107.1 11.18 1 54 1 0
#> 158 20.14 1 74 1 0
#> 90.2 20.94 1 50 0 1
#> 99 21.19 1 38 0 1
#> 96.1 14.54 1 33 0 1
#> 158.1 20.14 1 74 1 0
#> 167 15.55 1 56 1 0
#> 195 11.76 1 NA 1 0
#> 37.1 12.52 1 57 1 0
#> 110 17.56 1 65 0 1
#> 127.2 3.53 1 62 0 1
#> 187.1 9.92 1 39 1 0
#> 192 16.44 1 31 1 0
#> 32.1 20.90 1 37 1 0
#> 36 21.19 1 48 0 1
#> 128 20.35 1 35 0 1
#> 90.3 20.94 1 50 0 1
#> 136 21.83 1 43 0 1
#> 50 10.02 1 NA 1 0
#> 100.1 16.07 1 60 0 0
#> 86.1 23.81 1 58 0 1
#> 158.2 20.14 1 74 1 0
#> 154 12.63 1 20 1 0
#> 111 17.45 1 47 0 1
#> 90.4 20.94 1 50 0 1
#> 61.1 10.12 1 36 0 1
#> 57.1 14.46 1 45 0 1
#> 127.3 3.53 1 62 0 1
#> 184 17.77 1 38 0 0
#> 117.1 17.46 1 26 0 1
#> 39 15.59 1 37 0 1
#> 171 16.57 1 41 0 1
#> 63.3 22.77 1 31 1 0
#> 79 16.23 1 54 1 0
#> 189.1 10.51 1 NA 1 0
#> 177.1 12.53 1 75 0 0
#> 40 18.00 1 28 1 0
#> 107.2 11.18 1 54 1 0
#> 159 10.55 1 50 0 1
#> 181.1 16.46 1 45 0 1
#> 184.1 17.77 1 38 0 0
#> 136.1 21.83 1 43 0 1
#> 63.4 22.77 1 31 1 0
#> 52.1 10.42 1 52 0 1
#> 41.1 18.02 1 40 1 0
#> 29 15.45 1 68 1 0
#> 127.4 3.53 1 62 0 1
#> 123 13.00 1 44 1 0
#> 177.2 12.53 1 75 0 0
#> 91.1 5.33 1 61 0 1
#> 197 21.60 1 69 1 0
#> 14.1 12.89 1 21 0 0
#> 24 23.89 1 38 0 0
#> 168 23.72 1 70 0 0
#> 39.1 15.59 1 37 0 1
#> 140.1 12.68 1 59 1 0
#> 137 24.00 0 45 1 0
#> 118 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 1 24.00 0 23 1 0
#> 84 24.00 0 39 0 1
#> 146 24.00 0 63 1 0
#> 83 24.00 0 6 0 0
#> 74 24.00 0 43 0 1
#> 122 24.00 0 66 0 0
#> 98 24.00 0 34 1 0
#> 103 24.00 0 56 1 0
#> 64 24.00 0 43 0 0
#> 137.1 24.00 0 45 1 0
#> 160 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 146.1 24.00 0 63 1 0
#> 73 24.00 0 NA 0 1
#> 172 24.00 0 41 0 0
#> 162 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 103.1 24.00 0 56 1 0
#> 65 24.00 0 57 1 0
#> 67 24.00 0 25 0 0
#> 148 24.00 0 61 1 0
#> 116 24.00 0 58 0 1
#> 84.1 24.00 0 39 0 1
#> 172.1 24.00 0 41 0 0
#> 196 24.00 0 19 0 0
#> 137.2 24.00 0 45 1 0
#> 193 24.00 0 45 0 1
#> 73.1 24.00 0 NA 0 1
#> 31 24.00 0 36 0 1
#> 182 24.00 0 35 0 0
#> 20.1 24.00 0 46 1 0
#> 65.1 24.00 0 57 1 0
#> 44 24.00 0 56 0 0
#> 156 24.00 0 50 1 0
#> 74.1 24.00 0 43 0 1
#> 80 24.00 0 41 0 0
#> 191 24.00 0 60 0 1
#> 146.2 24.00 0 63 1 0
#> 104 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 148.1 24.00 0 61 1 0
#> 83.1 24.00 0 6 0 0
#> 27 24.00 0 63 1 0
#> 38 24.00 0 31 1 0
#> 116.1 24.00 0 58 0 1
#> 109 24.00 0 48 0 0
#> 84.2 24.00 0 39 0 1
#> 148.2 24.00 0 61 1 0
#> 67.1 24.00 0 25 0 0
#> 143.1 24.00 0 51 0 0
#> 31.1 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 67.2 24.00 0 25 0 0
#> 87 24.00 0 27 0 0
#> 196.1 24.00 0 19 0 0
#> 33 24.00 0 53 0 0
#> 12 24.00 0 63 0 0
#> 112 24.00 0 61 0 0
#> 35 24.00 0 51 0 0
#> 98.1 24.00 0 34 1 0
#> 98.2 24.00 0 34 1 0
#> 156.1 24.00 0 50 1 0
#> 131 24.00 0 66 0 0
#> 102 24.00 0 49 0 0
#> 17 24.00 0 38 0 1
#> 67.3 24.00 0 25 0 0
#> 12.1 24.00 0 63 0 0
#> 120 24.00 0 68 0 1
#> 74.2 24.00 0 43 0 1
#> 11.1 24.00 0 42 0 1
#> 62 24.00 0 71 0 0
#> 72 24.00 0 40 0 1
#> 64.1 24.00 0 43 0 0
#> 109.1 24.00 0 48 0 0
#> 75 24.00 0 21 1 0
#> 27.1 24.00 0 63 1 0
#> 33.1 24.00 0 53 0 0
#> 143.2 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 163 24.00 0 66 0 0
#> 83.2 24.00 0 6 0 0
#> 27.2 24.00 0 63 1 0
#> 98.3 24.00 0 34 1 0
#> 2 24.00 0 9 0 0
#> 46 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.44 NA NA NA
#> 2 age, Cure model 0.0170 NA NA NA
#> 3 grade_ii, Cure model 0.818 NA NA NA
#> 4 grade_iii, Cure model 1.58 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00350 NA NA NA
#> 2 grade_ii, Survival model 0.162 NA NA NA
#> 3 grade_iii, Survival model 0.160 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.44453 0.01703 0.81803 1.57530
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 240.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.44452706 0.01703031 0.81802622 1.57530277
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003504025 0.161607320 0.160286119
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.91383851 0.45547490 0.77736041 0.67308508 0.64823001 0.93585220
#> [7] 0.80075644 0.12902218 0.62306635 0.14572767 0.14572767 0.14572767
#> [13] 0.47386259 0.25467657 0.36886101 0.05610145 0.82376143 0.38859472
#> [19] 0.47386259 0.96490331 0.58898195 0.73790814 0.94316759 0.44604614
#> [25] 0.25467657 0.32065307 0.88422511 0.60619573 0.40841961 0.76163504
#> [31] 0.83904595 0.11144757 0.50098225 0.20446337 0.25467657 0.56303545
#> [37] 0.89907225 0.92122320 0.49190394 0.32065307 0.71389903 0.95046489
#> [43] 0.96490331 0.51004108 0.28777829 0.84669599 0.45547490 0.65658299
#> [49] 0.72196966 0.85431480 0.85431480 0.41824825 0.32065307 0.29907295
#> [55] 0.72196966 0.41824825 0.69763921 0.82376143 0.55424668 0.96490331
#> [61] 0.92122320 0.62306635 0.36886101 0.29907295 0.39854747 0.32065307
#> [67] 0.21771235 0.65658299 0.05610145 0.41824825 0.79294539 0.58032281
#> [73] 0.32065307 0.89907225 0.73790814 0.96490331 0.53667747 0.56303545
#> [79] 0.68134721 0.59761085 0.14572767 0.63983603 0.80075644 0.52777796
#> [85] 0.85431480 0.87671842 0.60619573 0.53667747 0.21771235 0.14572767
#> [91] 0.88422511 0.51004108 0.70579214 0.96490331 0.75371880 0.80075644
#> [97] 0.95046489 0.24234813 0.76163504 0.02337882 0.09227510 0.68134721
#> [103] 0.77736041 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 145 170 140 26 188 183 177 92 85 63 63.1 63.2 55
#> 10.07 19.54 12.68 15.77 16.16 9.24 12.53 22.92 16.44 22.77 22.77 22.77 19.34
#> 139 32 86 37 68 55.1 127 23 57 149 166 139.1 90
#> 21.49 20.90 23.81 12.52 20.62 19.34 3.53 16.92 14.46 8.37 19.98 21.49 20.94
#> 52 181 150 14 49 164 8 175 139.2 117 61 187 179
#> 10.42 16.46 20.33 12.89 12.19 23.60 18.43 21.91 21.49 17.46 10.12 9.92 18.63
#> 90.1 18 91 127.1 41 153 43 170.1 100 96 107 107.1 158
#> 20.94 15.21 5.33 3.53 18.02 21.33 12.10 19.54 16.07 14.54 11.18 11.18 20.14
#> 90.2 99 96.1 158.1 167 37.1 110 127.2 187.1 192 32.1 36 128
#> 20.94 21.19 14.54 20.14 15.55 12.52 17.56 3.53 9.92 16.44 20.90 21.19 20.35
#> 90.3 136 100.1 86.1 158.2 154 111 90.4 61.1 57.1 127.3 184 117.1
#> 20.94 21.83 16.07 23.81 20.14 12.63 17.45 20.94 10.12 14.46 3.53 17.77 17.46
#> 39 171 63.3 79 177.1 40 107.2 159 181.1 184.1 136.1 63.4 52.1
#> 15.59 16.57 22.77 16.23 12.53 18.00 11.18 10.55 16.46 17.77 21.83 22.77 10.42
#> 41.1 29 127.4 123 177.2 91.1 197 14.1 24 168 39.1 140.1 137
#> 18.02 15.45 3.53 13.00 12.53 5.33 21.60 12.89 23.89 23.72 15.59 12.68 24.00
#> 118 20 1 84 146 83 74 122 98 103 64 137.1 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 146.1 172 162 11 103.1 65 67 148 116 84.1 172.1 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.2 193 31 182 20.1 65.1 44 156 74.1 80 191 146.2 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 148.1 83.1 27 38 116.1 109 84.2 148.2 67.1 143.1 31.1 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.2 87 196.1 33 12 112 35 98.1 98.2 156.1 131 102 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.3 12.1 120 74.2 11.1 62 72 64.1 109.1 75 27.1 33.1 143.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 163 83.2 27.2 98.3 2 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[86]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01062233 0.70978667 0.44223944
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.65733481 0.01314944 -0.24328840
#> grade_iii, Cure model
#> 1.11290945
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 61 10.12 1 36 0 1
#> 166 19.98 1 48 0 0
#> 181 16.46 1 45 0 1
#> 30 17.43 1 78 0 0
#> 76 19.22 1 54 0 1
#> 192 16.44 1 31 1 0
#> 58 19.34 1 39 0 0
#> 101 9.97 1 10 0 1
#> 26 15.77 1 49 0 1
#> 136 21.83 1 43 0 1
#> 197 21.60 1 69 1 0
#> 136.1 21.83 1 43 0 1
#> 24 23.89 1 38 0 0
#> 168 23.72 1 70 0 0
#> 192.1 16.44 1 31 1 0
#> 85 16.44 1 36 0 0
#> 179 18.63 1 42 0 0
#> 4 17.64 1 NA 0 1
#> 123 13.00 1 44 1 0
#> 157 15.10 1 47 0 0
#> 117 17.46 1 26 0 1
#> 123.1 13.00 1 44 1 0
#> 59 10.16 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 13 14.34 1 54 0 1
#> 99 21.19 1 38 0 1
#> 14 12.89 1 21 0 0
#> 56 12.21 1 60 0 0
#> 190 20.81 1 42 1 0
#> 6 15.64 1 39 0 0
#> 16 8.71 1 71 0 1
#> 96 14.54 1 33 0 1
#> 59.1 10.16 1 NA 1 0
#> 166.1 19.98 1 48 0 0
#> 111 17.45 1 47 0 1
#> 4.1 17.64 1 NA 0 1
#> 190.1 20.81 1 42 1 0
#> 56.1 12.21 1 60 0 0
#> 168.1 23.72 1 70 0 0
#> 96.1 14.54 1 33 0 1
#> 79 16.23 1 54 1 0
#> 16.1 8.71 1 71 0 1
#> 97 19.14 1 65 0 1
#> 5 16.43 1 51 0 1
#> 117.1 17.46 1 26 0 1
#> 123.2 13.00 1 44 1 0
#> 92 22.92 1 47 0 1
#> 194 22.40 1 38 0 1
#> 99.1 21.19 1 38 0 1
#> 50 10.02 1 NA 1 0
#> 24.1 23.89 1 38 0 0
#> 10 10.53 1 34 0 0
#> 192.2 16.44 1 31 1 0
#> 90 20.94 1 50 0 1
#> 25 6.32 1 34 1 0
#> 189 10.51 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 93 10.33 1 52 0 1
#> 166.2 19.98 1 48 0 0
#> 190.2 20.81 1 42 1 0
#> 166.3 19.98 1 48 0 0
#> 167 15.55 1 56 1 0
#> 168.2 23.72 1 70 0 0
#> 50.1 10.02 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 108 18.29 1 39 0 1
#> 175 21.91 1 43 0 0
#> 168.3 23.72 1 70 0 0
#> 125 15.65 1 67 1 0
#> 88 18.37 1 47 0 0
#> 89 11.44 1 NA 0 0
#> 190.3 20.81 1 42 1 0
#> 8 18.43 1 32 0 0
#> 159 10.55 1 50 0 1
#> 128 20.35 1 35 0 1
#> 66 22.13 1 53 0 0
#> 190.4 20.81 1 42 1 0
#> 164 23.60 1 76 0 1
#> 90.1 20.94 1 50 0 1
#> 85.1 16.44 1 36 0 0
#> 42 12.43 1 49 0 1
#> 139 21.49 1 63 1 0
#> 68 20.62 1 44 0 0
#> 171 16.57 1 41 0 1
#> 181.1 16.46 1 45 0 1
#> 18 15.21 1 49 1 0
#> 39 15.59 1 37 0 1
#> 170 19.54 1 43 0 1
#> 129 23.41 1 53 1 0
#> 39.1 15.59 1 37 0 1
#> 140 12.68 1 59 1 0
#> 42.1 12.43 1 49 0 1
#> 110 17.56 1 65 0 1
#> 41 18.02 1 40 1 0
#> 170.1 19.54 1 43 0 1
#> 158 20.14 1 74 1 0
#> 18.1 15.21 1 49 1 0
#> 130 16.47 1 53 0 1
#> 140.1 12.68 1 59 1 0
#> 40.1 18.00 1 28 1 0
#> 92.1 22.92 1 47 0 1
#> 136.2 21.83 1 43 0 1
#> 56.2 12.21 1 60 0 0
#> 140.2 12.68 1 59 1 0
#> 157.1 15.10 1 47 0 0
#> 171.1 16.57 1 41 0 1
#> 145 10.07 1 65 1 0
#> 108.1 18.29 1 39 0 1
#> 100 16.07 1 60 0 0
#> 123.3 13.00 1 44 1 0
#> 78 23.88 1 43 0 0
#> 114 13.68 1 NA 0 0
#> 165 24.00 0 47 0 0
#> 17 24.00 0 38 0 1
#> 31 24.00 0 36 0 1
#> 104 24.00 0 50 1 0
#> 54 24.00 0 53 1 0
#> 200 24.00 0 64 0 0
#> 142 24.00 0 53 0 0
#> 28 24.00 0 67 1 0
#> 33 24.00 0 53 0 0
#> 121 24.00 0 57 1 0
#> 1 24.00 0 23 1 0
#> 116 24.00 0 58 0 1
#> 182 24.00 0 35 0 0
#> 67 24.00 0 25 0 0
#> 31.1 24.00 0 36 0 1
#> 109 24.00 0 48 0 0
#> 163 24.00 0 66 0 0
#> 138 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 22 24.00 0 52 1 0
#> 174 24.00 0 49 1 0
#> 82 24.00 0 34 0 0
#> 71 24.00 0 51 0 0
#> 1.1 24.00 0 23 1 0
#> 47.1 24.00 0 38 0 1
#> 115 24.00 0 NA 1 0
#> 71.1 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#> 103 24.00 0 56 1 0
#> 126 24.00 0 48 0 0
#> 186 24.00 0 45 1 0
#> 116.1 24.00 0 58 0 1
#> 200.1 24.00 0 64 0 0
#> 119 24.00 0 17 0 0
#> 94 24.00 0 51 0 1
#> 165.1 24.00 0 47 0 0
#> 3 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 71.2 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 3.1 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 103.1 24.00 0 56 1 0
#> 1.2 24.00 0 23 1 0
#> 172 24.00 0 41 0 0
#> 11 24.00 0 42 0 1
#> 174.1 24.00 0 49 1 0
#> 193 24.00 0 45 0 1
#> 54.1 24.00 0 53 1 0
#> 27 24.00 0 63 1 0
#> 143 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 48 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 102.1 24.00 0 49 0 0
#> 38.1 24.00 0 31 1 0
#> 102.2 24.00 0 49 0 0
#> 75.1 24.00 0 21 1 0
#> 138.1 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 198 24.00 0 66 0 1
#> 20.1 24.00 0 46 1 0
#> 176 24.00 0 43 0 1
#> 112 24.00 0 61 0 0
#> 65.1 24.00 0 57 1 0
#> 73 24.00 0 NA 0 1
#> 48.1 24.00 0 31 1 0
#> 121.1 24.00 0 57 1 0
#> 22.1 24.00 0 52 1 0
#> 34 24.00 0 36 0 0
#> 196 24.00 0 19 0 0
#> 19 24.00 0 57 0 1
#> 200.2 24.00 0 64 0 0
#> 160 24.00 0 31 1 0
#> 165.2 24.00 0 47 0 0
#> 119.1 24.00 0 17 0 0
#> 174.2 24.00 0 49 1 0
#> 163.1 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 19.1 24.00 0 57 0 1
#> 103.2 24.00 0 56 1 0
#> 54.2 24.00 0 53 1 0
#> 17.1 24.00 0 38 0 1
#> 146 24.00 0 63 1 0
#> 9 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.657 NA NA NA
#> 2 age, Cure model 0.0131 NA NA NA
#> 3 grade_ii, Cure model -0.243 NA NA NA
#> 4 grade_iii, Cure model 1.11 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0106 NA NA NA
#> 2 grade_ii, Survival model 0.710 NA NA NA
#> 3 grade_iii, Survival model 0.442 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.65733 0.01315 -0.24329 1.11291
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 245.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.65733481 0.01314944 -0.24328840 1.11290945
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01062233 0.70978667 0.44223944
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.937759587 0.277198773 0.541311149 0.500113471 0.355512532 0.561870731
#> [7] 0.345290388 0.958560909 0.641895394 0.116518942 0.145155982 0.116518942
#> [13] 0.001965466 0.020838250 0.561870731 0.561870731 0.376093125 0.775329839
#> [19] 0.723928631 0.469660384 0.775329839 0.439079039 0.764991019 0.165667645
#> [25] 0.815292732 0.875892917 0.205371246 0.662465659 0.968915594 0.744486994
#> [31] 0.277198773 0.489883510 0.205371246 0.875892917 0.020838250 0.744486994
#> [37] 0.621428370 0.968915594 0.365771005 0.611209478 0.469660384 0.775329839
#> [43] 0.068251305 0.086471027 0.165667645 0.001965466 0.916953973 0.561870731
#> [49] 0.185428145 0.989632343 0.014597584 0.927350695 0.277198773 0.205371246
#> [55] 0.277198773 0.693294506 0.020838250 0.315225398 0.407642241 0.106117881
#> [61] 0.020838250 0.652180370 0.397025020 0.205371246 0.386518235 0.906592863
#> [67] 0.258247718 0.096078119 0.205371246 0.048707612 0.185428145 0.561870731
#> [73] 0.855641407 0.155425699 0.248759180 0.510462687 0.541311149 0.703597210
#> [79] 0.672805400 0.325346007 0.058606044 0.672805400 0.825498010 0.855641407
#> [85] 0.459356608 0.428569879 0.325346007 0.267710915 0.703597210 0.530945862
#> [91] 0.825498010 0.439079039 0.068251305 0.116518942 0.875892917 0.825498010
#> [97] 0.723928631 0.510462687 0.948161361 0.407642241 0.631622810 0.775329839
#> [103] 0.008784661 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 61 166 181 30 76 192 58 101 26 136 197 136.1 24
#> 10.12 19.98 16.46 17.43 19.22 16.44 19.34 9.97 15.77 21.83 21.60 21.83 23.89
#> 168 192.1 85 179 123 157 117 123.1 40 13 99 14 56
#> 23.72 16.44 16.44 18.63 13.00 15.10 17.46 13.00 18.00 14.34 21.19 12.89 12.21
#> 190 6 16 96 166.1 111 190.1 56.1 168.1 96.1 79 16.1 97
#> 20.81 15.64 8.71 14.54 19.98 17.45 20.81 12.21 23.72 14.54 16.23 8.71 19.14
#> 5 117.1 123.2 92 194 99.1 24.1 10 192.2 90 25 86 93
#> 16.43 17.46 13.00 22.92 22.40 21.19 23.89 10.53 16.44 20.94 6.32 23.81 10.33
#> 166.2 190.2 166.3 167 168.2 105 108 175 168.3 125 88 190.3 8
#> 19.98 20.81 19.98 15.55 23.72 19.75 18.29 21.91 23.72 15.65 18.37 20.81 18.43
#> 159 128 66 190.4 164 90.1 85.1 42 139 68 171 181.1 18
#> 10.55 20.35 22.13 20.81 23.60 20.94 16.44 12.43 21.49 20.62 16.57 16.46 15.21
#> 39 170 129 39.1 140 42.1 110 41 170.1 158 18.1 130 140.1
#> 15.59 19.54 23.41 15.59 12.68 12.43 17.56 18.02 19.54 20.14 15.21 16.47 12.68
#> 40.1 92.1 136.2 56.2 140.2 157.1 171.1 145 108.1 100 123.3 78 165
#> 18.00 22.92 21.83 12.21 12.68 15.10 16.57 10.07 18.29 16.07 13.00 23.88 24.00
#> 17 31 104 54 200 142 28 33 121 1 116 182 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.1 109 163 138 38 47 22 174 82 71 1.1 47.1 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 103 126 186 116.1 200.1 119 94 165.1 3 151 71.2 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 185 75 103.1 1.2 172 11 174.1 193 54.1 27 143 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 2 102.1 38.1 102.2 75.1 138.1 80 198 20.1 176 112 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.1 121.1 22.1 34 196 19 200.2 160 165.2 119.1 174.2 163.1 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.1 103.2 54.2 17.1 146 9 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[87]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006451547 0.737673132 0.533646911
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.55107917 0.01261155 0.11860577
#> grade_iii, Cure model
#> 0.38439801
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 56 12.21 1 60 0 0
#> 25 6.32 1 34 1 0
#> 169 22.41 1 46 0 0
#> 181 16.46 1 45 0 1
#> 32 20.90 1 37 1 0
#> 81 14.06 1 34 0 0
#> 167 15.55 1 56 1 0
#> 197 21.60 1 69 1 0
#> 125 15.65 1 67 1 0
#> 164 23.60 1 76 0 1
#> 68 20.62 1 44 0 0
#> 61 10.12 1 36 0 1
#> 169.1 22.41 1 46 0 0
#> 140 12.68 1 59 1 0
#> 92 22.92 1 47 0 1
#> 24 23.89 1 38 0 0
#> 60 13.15 1 38 1 0
#> 16 8.71 1 71 0 1
#> 155 13.08 1 26 0 0
#> 184 17.77 1 38 0 0
#> 192 16.44 1 31 1 0
#> 41 18.02 1 40 1 0
#> 101 9.97 1 10 0 1
#> 40 18.00 1 28 1 0
#> 181.1 16.46 1 45 0 1
#> 150 20.33 1 48 0 0
#> 111 17.45 1 47 0 1
#> 8 18.43 1 32 0 0
#> 106 16.67 1 49 1 0
#> 24.1 23.89 1 38 0 0
#> 78 23.88 1 43 0 0
#> 49 12.19 1 48 1 0
#> 78.1 23.88 1 43 0 0
#> 107 11.18 1 54 1 0
#> 195 11.76 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 129 23.41 1 53 1 0
#> 29 15.45 1 68 1 0
#> 59 10.16 1 NA 1 0
#> 129.1 23.41 1 53 1 0
#> 101.1 9.97 1 10 0 1
#> 41.1 18.02 1 40 1 0
#> 88 18.37 1 47 0 0
#> 50 10.02 1 NA 1 0
#> 43 12.10 1 61 0 1
#> 130.1 16.47 1 53 0 1
#> 136 21.83 1 43 0 1
#> 97 19.14 1 65 0 1
#> 164.1 23.60 1 76 0 1
#> 57 14.46 1 45 0 1
#> 123 13.00 1 44 1 0
#> 68.1 20.62 1 44 0 0
#> 10 10.53 1 34 0 0
#> 190 20.81 1 42 1 0
#> 39 15.59 1 37 0 1
#> 100 16.07 1 60 0 0
#> 37 12.52 1 57 1 0
#> 50.1 10.02 1 NA 1 0
#> 57.1 14.46 1 45 0 1
#> 111.1 17.45 1 47 0 1
#> 15 22.68 1 48 0 0
#> 32.1 20.90 1 37 1 0
#> 86 23.81 1 58 0 1
#> 130.2 16.47 1 53 0 1
#> 145 10.07 1 65 1 0
#> 30 17.43 1 78 0 0
#> 40.1 18.00 1 28 1 0
#> 136.1 21.83 1 43 0 1
#> 58 19.34 1 39 0 0
#> 16.1 8.71 1 71 0 1
#> 70 7.38 1 30 1 0
#> 106.1 16.67 1 49 1 0
#> 69 23.23 1 25 0 1
#> 63 22.77 1 31 1 0
#> 60.1 13.15 1 38 1 0
#> 97.1 19.14 1 65 0 1
#> 155.1 13.08 1 26 0 0
#> 140.1 12.68 1 59 1 0
#> 79 16.23 1 54 1 0
#> 55 19.34 1 69 0 1
#> 140.2 12.68 1 59 1 0
#> 88.1 18.37 1 47 0 0
#> 76 19.22 1 54 0 1
#> 88.2 18.37 1 47 0 0
#> 154 12.63 1 20 1 0
#> 97.2 19.14 1 65 0 1
#> 92.1 22.92 1 47 0 1
#> 158 20.14 1 74 1 0
#> 108 18.29 1 39 0 1
#> 10.1 10.53 1 34 0 0
#> 168 23.72 1 70 0 0
#> 134 17.81 1 47 1 0
#> 157 15.10 1 47 0 0
#> 57.2 14.46 1 45 0 1
#> 24.2 23.89 1 38 0 0
#> 124 9.73 1 NA 1 0
#> 55.1 19.34 1 69 0 1
#> 195.1 11.76 1 NA 1 0
#> 93 10.33 1 52 0 1
#> 133 14.65 1 57 0 0
#> 127 3.53 1 62 0 1
#> 187 9.92 1 39 1 0
#> 177 12.53 1 75 0 0
#> 88.3 18.37 1 47 0 0
#> 145.1 10.07 1 65 1 0
#> 56.1 12.21 1 60 0 0
#> 52 10.42 1 52 0 1
#> 70.1 7.38 1 30 1 0
#> 149 8.37 1 33 1 0
#> 129.2 23.41 1 53 1 0
#> 189 10.51 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 102 24.00 0 49 0 0
#> 163 24.00 0 66 0 0
#> 182 24.00 0 35 0 0
#> 7 24.00 0 37 1 0
#> 46 24.00 0 71 0 0
#> 84 24.00 0 39 0 1
#> 31 24.00 0 36 0 1
#> 19 24.00 0 57 0 1
#> 82 24.00 0 34 0 0
#> 121 24.00 0 57 1 0
#> 102.1 24.00 0 49 0 0
#> 141 24.00 0 44 1 0
#> 185 24.00 0 44 1 0
#> 84.1 24.00 0 39 0 1
#> 174 24.00 0 49 1 0
#> 198 24.00 0 66 0 1
#> 98 24.00 0 34 1 0
#> 20 24.00 0 46 1 0
#> 44 24.00 0 56 0 0
#> 22 24.00 0 52 1 0
#> 122 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 82.1 24.00 0 34 0 0
#> 75 24.00 0 21 1 0
#> 73 24.00 0 NA 0 1
#> 47 24.00 0 38 0 1
#> 116 24.00 0 58 0 1
#> 137 24.00 0 45 1 0
#> 162 24.00 0 51 0 0
#> 146.1 24.00 0 63 1 0
#> 2 24.00 0 9 0 0
#> 143 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 1 24.00 0 23 1 0
#> 46.1 24.00 0 71 0 0
#> 174.1 24.00 0 49 1 0
#> 116.1 24.00 0 58 0 1
#> 83 24.00 0 6 0 0
#> 143.1 24.00 0 51 0 0
#> 31.1 24.00 0 36 0 1
#> 98.1 24.00 0 34 1 0
#> 20.1 24.00 0 46 1 0
#> 3 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 191 24.00 0 60 0 1
#> 65 24.00 0 57 1 0
#> 165 24.00 0 47 0 0
#> 191.1 24.00 0 60 0 1
#> 141.1 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 7.1 24.00 0 37 1 0
#> 196 24.00 0 19 0 0
#> 62 24.00 0 71 0 0
#> 119 24.00 0 17 0 0
#> 34 24.00 0 36 0 0
#> 161 24.00 0 45 0 0
#> 7.2 24.00 0 37 1 0
#> 193 24.00 0 45 0 1
#> 115 24.00 0 NA 1 0
#> 193.1 24.00 0 45 0 1
#> 152 24.00 0 36 0 1
#> 109 24.00 0 48 0 0
#> 44.1 24.00 0 56 0 0
#> 138 24.00 0 44 1 0
#> 137.1 24.00 0 45 1 0
#> 9 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 144 24.00 0 28 0 1
#> 84.2 24.00 0 39 0 1
#> 103 24.00 0 56 1 0
#> 120 24.00 0 68 0 1
#> 19.1 24.00 0 57 0 1
#> 121.1 24.00 0 57 1 0
#> 141.2 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 64 24.00 0 43 0 0
#> 94 24.00 0 51 0 1
#> 172 24.00 0 41 0 0
#> 46.2 24.00 0 71 0 0
#> 138.1 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 34.1 24.00 0 36 0 0
#> 74.1 24.00 0 43 0 1
#> 27 24.00 0 63 1 0
#> 31.2 24.00 0 36 0 1
#> 138.2 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 118 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.551 NA NA NA
#> 2 age, Cure model 0.0126 NA NA NA
#> 3 grade_ii, Cure model 0.119 NA NA NA
#> 4 grade_iii, Cure model 0.384 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00645 NA NA NA
#> 2 grade_ii, Survival model 0.738 NA NA NA
#> 3 grade_iii, Survival model 0.534 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.55108 0.01261 0.11861 0.38440
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 260.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.55107917 0.01261155 0.11860577 0.38439801
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006451547 0.737673132 0.533646911
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.82056712 0.98423850 0.20744508 0.58719707 0.26085333 0.71910465
#> [7] 0.64955718 0.25022649 0.63185568 0.09233103 0.29052295 0.89546257
#> [13] 0.20744508 0.77049788 0.16431322 0.01053816 0.72780699 0.94434872
#> [19] 0.74484982 0.50474328 0.60512647 0.45729045 0.92008591 0.47661442
#> [25] 0.58719707 0.31025379 0.51415292 0.39831441 0.54200964 0.01053816
#> [31] 0.03781960 0.83727564 0.03781960 0.85396650 0.56028478 0.11947061
#> [37] 0.65833245 0.11947061 0.92008591 0.45729045 0.40819483 0.84562727
#> [43] 0.56028478 0.22912640 0.36953222 0.09233103 0.68463169 0.76195310
#> [49] 0.29052295 0.86226716 0.28065291 0.64072740 0.62293925 0.81222471
#> [55] 0.68463169 0.51415292 0.19660526 0.26085333 0.06346767 0.56028478
#> [61] 0.90373280 0.53262645 0.47661442 0.22912640 0.33038886 0.94434872
#> [67] 0.96844564 0.54200964 0.15272143 0.18592240 0.72780699 0.36953222
#> [73] 0.74484982 0.77049788 0.61406360 0.33038886 0.77049788 0.40819483
#> [79] 0.35958171 0.40819483 0.79549619 0.36953222 0.16431322 0.32036833
#> [85] 0.44726059 0.86226716 0.07740855 0.49537164 0.66706714 0.68463169
#> [91] 0.01053816 0.33038886 0.88716539 0.67583186 0.99212373 0.93626688
#> [97] 0.80384376 0.40819483 0.90373280 0.82056712 0.87885117 0.96844564
#> [103] 0.96042175 0.11947061 0.71042301 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 56 25 169 181 32 81 167 197 125 164 68 61 169.1
#> 12.21 6.32 22.41 16.46 20.90 14.06 15.55 21.60 15.65 23.60 20.62 10.12 22.41
#> 140 92 24 60 16 155 184 192 41 101 40 181.1 150
#> 12.68 22.92 23.89 13.15 8.71 13.08 17.77 16.44 18.02 9.97 18.00 16.46 20.33
#> 111 8 106 24.1 78 49 78.1 107 130 129 29 129.1 101.1
#> 17.45 18.43 16.67 23.89 23.88 12.19 23.88 11.18 16.47 23.41 15.45 23.41 9.97
#> 41.1 88 43 130.1 136 97 164.1 57 123 68.1 10 190 39
#> 18.02 18.37 12.10 16.47 21.83 19.14 23.60 14.46 13.00 20.62 10.53 20.81 15.59
#> 100 37 57.1 111.1 15 32.1 86 130.2 145 30 40.1 136.1 58
#> 16.07 12.52 14.46 17.45 22.68 20.90 23.81 16.47 10.07 17.43 18.00 21.83 19.34
#> 16.1 70 106.1 69 63 60.1 97.1 155.1 140.1 79 55 140.2 88.1
#> 8.71 7.38 16.67 23.23 22.77 13.15 19.14 13.08 12.68 16.23 19.34 12.68 18.37
#> 76 88.2 154 97.2 92.1 158 108 10.1 168 134 157 57.2 24.2
#> 19.22 18.37 12.63 19.14 22.92 20.14 18.29 10.53 23.72 17.81 15.10 14.46 23.89
#> 55.1 93 133 127 187 177 88.3 145.1 56.1 52 70.1 149 129.2
#> 19.34 10.33 14.65 3.53 9.92 12.53 18.37 10.07 12.21 10.42 7.38 8.37 23.41
#> 13 102 163 182 7 46 84 31 19 82 121 102.1 141
#> 14.34 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 84.1 174 198 98 20 44 22 122 146 82.1 75 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 137 162 146.1 2 143 126 1 46.1 174.1 116.1 83 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.1 98.1 20.1 3 142 191 65 165 191.1 141.1 112 7.1 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 119 34 161 7.2 193 193.1 152 109 44.1 138 137.1 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.1 144 84.2 103 120 19.1 121.1 141.2 104 64 94 172 46.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.1 74 34.1 74.1 27 31.2 138.2 173 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[88]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01197838 1.05243939 0.69982911
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.97242228 0.02400026 -0.32973675
#> grade_iii, Cure model
#> 0.33043035
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 93 10.33 1 52 0 1
#> 166 19.98 1 48 0 0
#> 187 9.92 1 39 1 0
#> 154 12.63 1 20 1 0
#> 171 16.57 1 41 0 1
#> 136 21.83 1 43 0 1
#> 169 22.41 1 46 0 0
#> 23 16.92 1 61 0 0
#> 101 9.97 1 10 0 1
#> 6 15.64 1 39 0 0
#> 114 13.68 1 NA 0 0
#> 170 19.54 1 43 0 1
#> 23.1 16.92 1 61 0 0
#> 140 12.68 1 59 1 0
#> 81 14.06 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 149 8.37 1 33 1 0
#> 164 23.60 1 76 0 1
#> 59 10.16 1 NA 1 0
#> 23.2 16.92 1 61 0 0
#> 57 14.46 1 45 0 1
#> 105 19.75 1 60 0 0
#> 106 16.67 1 49 1 0
#> 166.1 19.98 1 48 0 0
#> 91 5.33 1 61 0 1
#> 81.1 14.06 1 34 0 0
#> 24 23.89 1 38 0 0
#> 77 7.27 1 67 0 1
#> 8 18.43 1 32 0 0
#> 164.1 23.60 1 76 0 1
#> 66 22.13 1 53 0 0
#> 149.1 8.37 1 33 1 0
#> 55 19.34 1 69 0 1
#> 197 21.60 1 69 1 0
#> 6.1 15.64 1 39 0 0
#> 24.1 23.89 1 38 0 0
#> 199 19.81 1 NA 0 1
#> 114.1 13.68 1 NA 0 0
#> 90 20.94 1 50 0 1
#> 89 11.44 1 NA 0 0
#> 197.1 21.60 1 69 1 0
#> 88 18.37 1 47 0 0
#> 79 16.23 1 54 1 0
#> 43 12.10 1 61 0 1
#> 164.2 23.60 1 76 0 1
#> 91.1 5.33 1 61 0 1
#> 140.1 12.68 1 59 1 0
#> 106.1 16.67 1 49 1 0
#> 45 17.42 1 54 0 1
#> 30 17.43 1 78 0 0
#> 57.1 14.46 1 45 0 1
#> 107 11.18 1 54 1 0
#> 14 12.89 1 21 0 0
#> 167 15.55 1 56 1 0
#> 58 19.34 1 39 0 0
#> 108 18.29 1 39 0 1
#> 90.1 20.94 1 50 0 1
#> 140.2 12.68 1 59 1 0
#> 30.1 17.43 1 78 0 0
#> 113 22.86 1 34 0 0
#> 106.2 16.67 1 49 1 0
#> 78 23.88 1 43 0 0
#> 110 17.56 1 65 0 1
#> 154.1 12.63 1 20 1 0
#> 130 16.47 1 53 0 1
#> 110.1 17.56 1 65 0 1
#> 159 10.55 1 50 0 1
#> 194 22.40 1 38 0 1
#> 189 10.51 1 NA 1 0
#> 114.2 13.68 1 NA 0 0
#> 68 20.62 1 44 0 0
#> 128 20.35 1 35 0 1
#> 129 23.41 1 53 1 0
#> 153 21.33 1 55 1 0
#> 105.1 19.75 1 60 0 0
#> 117 17.46 1 26 0 1
#> 105.2 19.75 1 60 0 0
#> 199.1 19.81 1 NA 0 1
#> 199.2 19.81 1 NA 0 1
#> 13 14.34 1 54 0 1
#> 40 18.00 1 28 1 0
#> 89.1 11.44 1 NA 0 0
#> 93.1 10.33 1 52 0 1
#> 8.1 18.43 1 32 0 0
#> 32 20.90 1 37 1 0
#> 36 21.19 1 48 0 1
#> 127 3.53 1 62 0 1
#> 24.2 23.89 1 38 0 0
#> 36.1 21.19 1 48 0 1
#> 37 12.52 1 57 1 0
#> 59.1 10.16 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 199.3 19.81 1 NA 0 1
#> 78.1 23.88 1 43 0 0
#> 97 19.14 1 65 0 1
#> 49 12.19 1 48 1 0
#> 26 15.77 1 49 0 1
#> 107.1 11.18 1 54 1 0
#> 113.1 22.86 1 34 0 0
#> 36.2 21.19 1 48 0 1
#> 145 10.07 1 65 1 0
#> 101.1 9.97 1 10 0 1
#> 124 9.73 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 110.2 17.56 1 65 0 1
#> 123 13.00 1 44 1 0
#> 140.3 12.68 1 59 1 0
#> 188 16.16 1 46 0 1
#> 150 20.33 1 48 0 0
#> 6.2 15.64 1 39 0 0
#> 153.1 21.33 1 55 1 0
#> 186 24.00 0 45 1 0
#> 98 24.00 0 34 1 0
#> 160 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 64 24.00 0 43 0 0
#> 1 24.00 0 23 1 0
#> 31 24.00 0 36 0 1
#> 176 24.00 0 43 0 1
#> 9 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 152 24.00 0 36 0 1
#> 115 24.00 0 NA 1 0
#> 186.1 24.00 0 45 1 0
#> 35 24.00 0 51 0 0
#> 120 24.00 0 68 0 1
#> 67 24.00 0 25 0 0
#> 196 24.00 0 19 0 0
#> 3 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 172 24.00 0 41 0 0
#> 126 24.00 0 48 0 0
#> 119 24.00 0 17 0 0
#> 137 24.00 0 45 1 0
#> 160.1 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 19 24.00 0 57 0 1
#> 65 24.00 0 57 1 0
#> 120.1 24.00 0 68 0 1
#> 1.1 24.00 0 23 1 0
#> 54 24.00 0 53 1 0
#> 65.1 24.00 0 57 1 0
#> 71 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 120.2 24.00 0 68 0 1
#> 198 24.00 0 66 0 1
#> 144 24.00 0 28 0 1
#> 21 24.00 0 47 0 0
#> 21.1 24.00 0 47 0 0
#> 144.1 24.00 0 28 0 1
#> 162 24.00 0 51 0 0
#> 82 24.00 0 34 0 0
#> 3.1 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 198.1 24.00 0 66 0 1
#> 200 24.00 0 64 0 0
#> 3.2 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 103 24.00 0 56 1 0
#> 104 24.00 0 50 1 0
#> 162.1 24.00 0 51 0 0
#> 176.1 24.00 0 43 0 1
#> 144.2 24.00 0 28 0 1
#> 109 24.00 0 48 0 0
#> 198.2 24.00 0 66 0 1
#> 9.1 24.00 0 31 1 0
#> 67.1 24.00 0 25 0 0
#> 132 24.00 0 55 0 0
#> 138.1 24.00 0 44 1 0
#> 146.1 24.00 0 63 1 0
#> 160.2 24.00 0 31 1 0
#> 109.1 24.00 0 48 0 0
#> 53 24.00 0 32 0 1
#> 103.1 24.00 0 56 1 0
#> 178 24.00 0 52 1 0
#> 94 24.00 0 51 0 1
#> 147 24.00 0 76 1 0
#> 142 24.00 0 53 0 0
#> 27 24.00 0 63 1 0
#> 31.1 24.00 0 36 0 1
#> 109.2 24.00 0 48 0 0
#> 72 24.00 0 40 0 1
#> 53.1 24.00 0 32 0 1
#> 115.1 24.00 0 NA 1 0
#> 174 24.00 0 49 1 0
#> 84 24.00 0 39 0 1
#> 191 24.00 0 60 0 1
#> 119.1 24.00 0 17 0 0
#> 21.2 24.00 0 47 0 0
#> 83.1 24.00 0 6 0 0
#> 137.1 24.00 0 45 1 0
#> 34 24.00 0 36 0 0
#> 196.1 24.00 0 19 0 0
#> 151 24.00 0 42 0 0
#> 104.1 24.00 0 50 1 0
#> 185 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 193 24.00 0 45 0 1
#> 156 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.972 NA NA NA
#> 2 age, Cure model 0.0240 NA NA NA
#> 3 grade_ii, Cure model -0.330 NA NA NA
#> 4 grade_iii, Cure model 0.330 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0120 NA NA NA
#> 2 grade_ii, Survival model 1.05 NA NA NA
#> 3 grade_iii, Survival model 0.700 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.9724 0.0240 -0.3297 0.3304
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 252.8
#> Residual Deviance: 243.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.97242228 0.02400026 -0.32973675 0.33043035
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01197838 1.05243939 0.69982911
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.886077435 0.287132282 0.934469674 0.796850149 0.574742282 0.136209672
#> [7] 0.100669817 0.509644443 0.915351037 0.638983217 0.338052843 0.509644443
#> [13] 0.755984725 0.713335046 0.628383195 0.944000436 0.039986839 0.509644443
#> [19] 0.681552636 0.307087991 0.542771263 0.287132282 0.971981373 0.713335046
#> [25] 0.004334045 0.962618171 0.380562625 0.039986839 0.124122470 0.944000436
#> [31] 0.348639024 0.148083867 0.638983217 0.004334045 0.228512250 0.148083867
#> [37] 0.402163838 0.596355967 0.836886689 0.039986839 0.971981373 0.755984725
#> [43] 0.542771263 0.498730178 0.477115057 0.681552636 0.846847426 0.745311366
#> [49] 0.670840826 0.348639024 0.413243382 0.228512250 0.755984725 0.477115057
#> [55] 0.079290207 0.542771263 0.020967133 0.434956775 0.796850149 0.585555816
#> [61] 0.434956775 0.866422779 0.112564695 0.257761195 0.267578129 0.068800007
#> [67] 0.170031798 0.307087991 0.466478273 0.307087991 0.702692947 0.424245671
#> [73] 0.886077435 0.380562625 0.248095096 0.190698210 0.990628451 0.004334045
#> [79] 0.190698210 0.816898502 0.190698210 0.020967133 0.369801715 0.826929554
#> [85] 0.617732174 0.846847426 0.079290207 0.190698210 0.905580002 0.915351037
#> [91] 0.876254514 0.434956775 0.734671895 0.755984725 0.607059166 0.277279826
#> [97] 0.638983217 0.170031798 0.000000000 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 93 166 187 154 171 136 169 23 101 6 170 23.1 140
#> 10.33 19.98 9.92 12.63 16.57 21.83 22.41 16.92 9.97 15.64 19.54 16.92 12.68
#> 81 125 149 164 23.2 57 105 106 166.1 91 81.1 24 77
#> 14.06 15.65 8.37 23.60 16.92 14.46 19.75 16.67 19.98 5.33 14.06 23.89 7.27
#> 8 164.1 66 149.1 55 197 6.1 24.1 90 197.1 88 79 43
#> 18.43 23.60 22.13 8.37 19.34 21.60 15.64 23.89 20.94 21.60 18.37 16.23 12.10
#> 164.2 91.1 140.1 106.1 45 30 57.1 107 14 167 58 108 90.1
#> 23.60 5.33 12.68 16.67 17.42 17.43 14.46 11.18 12.89 15.55 19.34 18.29 20.94
#> 140.2 30.1 113 106.2 78 110 154.1 130 110.1 159 194 68 128
#> 12.68 17.43 22.86 16.67 23.88 17.56 12.63 16.47 17.56 10.55 22.40 20.62 20.35
#> 129 153 105.1 117 105.2 13 40 93.1 8.1 32 36 127 24.2
#> 23.41 21.33 19.75 17.46 19.75 14.34 18.00 10.33 18.43 20.90 21.19 3.53 23.89
#> 36.1 37 99 78.1 97 49 26 107.1 113.1 36.2 145 101.1 52
#> 21.19 12.52 21.19 23.88 19.14 12.19 15.77 11.18 22.86 21.19 10.07 9.97 10.42
#> 110.2 123 140.3 188 150 6.2 153.1 186 98 160 83 64 1
#> 17.56 13.00 12.68 16.16 20.33 15.64 21.33 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 176 9 146 152 186.1 35 120 67 196 3 138 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 119 137 160.1 112 19 65 120.1 1.1 54 65.1 71 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.2 198 144 21 21.1 144.1 162 82 3.1 46 198.1 200 3.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 103 104 162.1 176.1 144.2 109 198.2 9.1 67.1 132 138.1 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.2 109.1 53 103.1 178 94 147 142 27 31.1 109.2 72 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 84 191 119.1 21.2 83.1 137.1 34 196.1 151 104.1 185 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[89]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004217649 0.710750429 0.377312454
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.064720085 -0.003914964 0.215507757
#> grade_iii, Cure model
#> 0.684409830
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 99 21.19 1 38 0 1
#> 99.1 21.19 1 38 0 1
#> 194 22.40 1 38 0 1
#> 180 14.82 1 37 0 0
#> 168 23.72 1 70 0 0
#> 81 14.06 1 34 0 0
#> 159 10.55 1 50 0 1
#> 184 17.77 1 38 0 0
#> 36 21.19 1 48 0 1
#> 166 19.98 1 48 0 0
#> 130 16.47 1 53 0 1
#> 189 10.51 1 NA 1 0
#> 168.1 23.72 1 70 0 0
#> 155 13.08 1 26 0 0
#> 199 19.81 1 NA 0 1
#> 127 3.53 1 62 0 1
#> 37 12.52 1 57 1 0
#> 90 20.94 1 50 0 1
#> 23 16.92 1 61 0 0
#> 25 6.32 1 34 1 0
#> 45 17.42 1 54 0 1
#> 30 17.43 1 78 0 0
#> 42 12.43 1 49 0 1
#> 167 15.55 1 56 1 0
#> 41 18.02 1 40 1 0
#> 190 20.81 1 42 1 0
#> 90.1 20.94 1 50 0 1
#> 6 15.64 1 39 0 0
#> 166.1 19.98 1 48 0 0
#> 127.1 3.53 1 62 0 1
#> 101 9.97 1 10 0 1
#> 134 17.81 1 47 1 0
#> 140 12.68 1 59 1 0
#> 96 14.54 1 33 0 1
#> 52 10.42 1 52 0 1
#> 30.1 17.43 1 78 0 0
#> 106 16.67 1 49 1 0
#> 45.1 17.42 1 54 0 1
#> 192 16.44 1 31 1 0
#> 56 12.21 1 60 0 0
#> 96.1 14.54 1 33 0 1
#> 130.1 16.47 1 53 0 1
#> 40 18.00 1 28 1 0
#> 187 9.92 1 39 1 0
#> 24 23.89 1 38 0 0
#> 49 12.19 1 48 1 0
#> 167.1 15.55 1 56 1 0
#> 192.1 16.44 1 31 1 0
#> 125 15.65 1 67 1 0
#> 5 16.43 1 51 0 1
#> 199.1 19.81 1 NA 0 1
#> 30.2 17.43 1 78 0 0
#> 189.1 10.51 1 NA 1 0
#> 32 20.90 1 37 1 0
#> 157 15.10 1 47 0 0
#> 92 22.92 1 47 0 1
#> 149 8.37 1 33 1 0
#> 49.1 12.19 1 48 1 0
#> 68 20.62 1 44 0 0
#> 170 19.54 1 43 0 1
#> 70 7.38 1 30 1 0
#> 10 10.53 1 34 0 0
#> 45.2 17.42 1 54 0 1
#> 24.1 23.89 1 38 0 0
#> 114 13.68 1 NA 0 0
#> 136 21.83 1 43 0 1
#> 167.2 15.55 1 56 1 0
#> 105 19.75 1 60 0 0
#> 45.3 17.42 1 54 0 1
#> 4 17.64 1 NA 0 1
#> 60 13.15 1 38 1 0
#> 125.1 15.65 1 67 1 0
#> 133 14.65 1 57 0 0
#> 49.2 12.19 1 48 1 0
#> 166.2 19.98 1 48 0 0
#> 13 14.34 1 54 0 1
#> 90.2 20.94 1 50 0 1
#> 188 16.16 1 46 0 1
#> 45.4 17.42 1 54 0 1
#> 39 15.59 1 37 0 1
#> 108 18.29 1 39 0 1
#> 197 21.60 1 69 1 0
#> 105.1 19.75 1 60 0 0
#> 52.1 10.42 1 52 0 1
#> 10.1 10.53 1 34 0 0
#> 18 15.21 1 49 1 0
#> 167.3 15.55 1 56 1 0
#> 123 13.00 1 44 1 0
#> 111 17.45 1 47 0 1
#> 130.2 16.47 1 53 0 1
#> 190.1 20.81 1 42 1 0
#> 181 16.46 1 45 0 1
#> 77 7.27 1 67 0 1
#> 56.1 12.21 1 60 0 0
#> 26 15.77 1 49 0 1
#> 159.1 10.55 1 50 0 1
#> 18.1 15.21 1 49 1 0
#> 158 20.14 1 74 1 0
#> 78 23.88 1 43 0 0
#> 93 10.33 1 52 0 1
#> 179 18.63 1 42 0 0
#> 117 17.46 1 26 0 1
#> 170.1 19.54 1 43 0 1
#> 55 19.34 1 69 0 1
#> 145 10.07 1 65 1 0
#> 129 23.41 1 53 1 0
#> 59 10.16 1 NA 1 0
#> 101.1 9.97 1 10 0 1
#> 158.1 20.14 1 74 1 0
#> 194.1 22.40 1 38 0 1
#> 149.1 8.37 1 33 1 0
#> 136.1 21.83 1 43 0 1
#> 44 24.00 0 56 0 0
#> 35 24.00 0 51 0 0
#> 53 24.00 0 32 0 1
#> 82 24.00 0 34 0 0
#> 120 24.00 0 68 0 1
#> 161 24.00 0 45 0 0
#> 122 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 74 24.00 0 43 0 1
#> 47 24.00 0 38 0 1
#> 34 24.00 0 36 0 0
#> 161.1 24.00 0 45 0 0
#> 74.1 24.00 0 43 0 1
#> 35.1 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 98 24.00 0 34 1 0
#> 20 24.00 0 46 1 0
#> 47.1 24.00 0 38 0 1
#> 191 24.00 0 60 0 1
#> 200 24.00 0 64 0 0
#> 95 24.00 0 68 0 1
#> 176 24.00 0 43 0 1
#> 31 24.00 0 36 0 1
#> 120.1 24.00 0 68 0 1
#> 20.1 24.00 0 46 1 0
#> 185 24.00 0 44 1 0
#> 122.1 24.00 0 66 0 0
#> 200.1 24.00 0 64 0 0
#> 22 24.00 0 52 1 0
#> 122.2 24.00 0 66 0 0
#> 1 24.00 0 23 1 0
#> 137 24.00 0 45 1 0
#> 28 24.00 0 67 1 0
#> 71 24.00 0 51 0 0
#> 74.2 24.00 0 43 0 1
#> 122.3 24.00 0 66 0 0
#> 142 24.00 0 53 0 0
#> 47.2 24.00 0 38 0 1
#> 48 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 103 24.00 0 56 1 0
#> 95.1 24.00 0 68 0 1
#> 163 24.00 0 66 0 0
#> 137.1 24.00 0 45 1 0
#> 143 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#> 146 24.00 0 63 1 0
#> 193 24.00 0 45 0 1
#> 38 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 31.1 24.00 0 36 0 1
#> 28.1 24.00 0 67 1 0
#> 94 24.00 0 51 0 1
#> 116 24.00 0 58 0 1
#> 152 24.00 0 36 0 1
#> 137.2 24.00 0 45 1 0
#> 27 24.00 0 63 1 0
#> 104 24.00 0 50 1 0
#> 173 24.00 0 19 0 1
#> 121 24.00 0 57 1 0
#> 20.2 24.00 0 46 1 0
#> 46 24.00 0 71 0 0
#> 71.1 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 20.3 24.00 0 46 1 0
#> 7 24.00 0 37 1 0
#> 109 24.00 0 48 0 0
#> 28.2 24.00 0 67 1 0
#> 21 24.00 0 47 0 0
#> 20.4 24.00 0 46 1 0
#> 198 24.00 0 66 0 1
#> 62 24.00 0 71 0 0
#> 75 24.00 0 21 1 0
#> 142.1 24.00 0 53 0 0
#> 174 24.00 0 49 1 0
#> 116.1 24.00 0 58 0 1
#> 186 24.00 0 45 1 0
#> 132.1 24.00 0 55 0 0
#> 102.1 24.00 0 49 0 0
#> 72 24.00 0 40 0 1
#> 151 24.00 0 42 0 0
#> 156 24.00 0 50 1 0
#> 73 24.00 0 NA 0 1
#> 62.1 24.00 0 71 0 0
#> 20.5 24.00 0 46 1 0
#> 138 24.00 0 44 1 0
#> 2 24.00 0 9 0 0
#> 48.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0647 NA NA NA
#> 2 age, Cure model -0.00391 NA NA NA
#> 3 grade_ii, Cure model 0.216 NA NA NA
#> 4 grade_iii, Cure model 0.684 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00422 NA NA NA
#> 2 grade_ii, Survival model 0.711 NA NA NA
#> 3 grade_iii, Survival model 0.377 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.064720 -0.003915 0.215508 0.684410
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 260.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.064720085 -0.003914964 0.215507757 0.684409830
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004217649 0.710750429 0.377312454
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.171044149 0.171044149 0.108038672 0.720349373 0.047606842 0.762077519
#> [7] 0.859643976 0.425210563 0.171044149 0.296937604 0.545916622 0.047606842
#> [13] 0.778706945 0.984865937 0.803410247 0.204128292 0.527151689 0.977255196
#> [19] 0.481807256 0.453630558 0.811541844 0.662055283 0.396234549 0.247143489
#> [25] 0.204128292 0.644493979 0.296937604 0.984865937 0.923118238 0.415713191
#> [31] 0.795228922 0.737133887 0.891406068 0.453630558 0.536587917 0.481807256
#> [37] 0.582410750 0.819658310 0.737133887 0.545916622 0.406068314 0.938766766
#> [43] 0.009925737 0.835882360 0.662055283 0.582410750 0.627059320 0.600248556
#> [49] 0.453630558 0.236282015 0.711981512 0.093364951 0.946576406 0.835882360
#> [55] 0.267176573 0.346281611 0.961936644 0.875505776 0.481807256 0.009925737
#> [61] 0.133851148 0.662055283 0.326197865 0.481807256 0.770425168 0.627059320
#> [67] 0.728731303 0.835882360 0.296937604 0.753742069 0.204128292 0.609211098
#> [73] 0.481807256 0.653289243 0.386222011 0.158646168 0.326197865 0.891406068
#> [79] 0.875505776 0.695379018 0.662055283 0.786997881 0.444204700 0.545916622
#> [85] 0.247143489 0.573199023 0.969598925 0.819658310 0.618147194 0.859643976
#> [91] 0.695379018 0.277454843 0.032103325 0.907257972 0.376147550 0.434739461
#> [97] 0.346281611 0.366116717 0.915206913 0.078230861 0.923118238 0.277454843
#> [103] 0.108038672 0.946576406 0.133851148 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 99 99.1 194 180 168 81 159 184 36 166 130 168.1 155
#> 21.19 21.19 22.40 14.82 23.72 14.06 10.55 17.77 21.19 19.98 16.47 23.72 13.08
#> 127 37 90 23 25 45 30 42 167 41 190 90.1 6
#> 3.53 12.52 20.94 16.92 6.32 17.42 17.43 12.43 15.55 18.02 20.81 20.94 15.64
#> 166.1 127.1 101 134 140 96 52 30.1 106 45.1 192 56 96.1
#> 19.98 3.53 9.97 17.81 12.68 14.54 10.42 17.43 16.67 17.42 16.44 12.21 14.54
#> 130.1 40 187 24 49 167.1 192.1 125 5 30.2 32 157 92
#> 16.47 18.00 9.92 23.89 12.19 15.55 16.44 15.65 16.43 17.43 20.90 15.10 22.92
#> 149 49.1 68 170 70 10 45.2 24.1 136 167.2 105 45.3 60
#> 8.37 12.19 20.62 19.54 7.38 10.53 17.42 23.89 21.83 15.55 19.75 17.42 13.15
#> 125.1 133 49.2 166.2 13 90.2 188 45.4 39 108 197 105.1 52.1
#> 15.65 14.65 12.19 19.98 14.34 20.94 16.16 17.42 15.59 18.29 21.60 19.75 10.42
#> 10.1 18 167.3 123 111 130.2 190.1 181 77 56.1 26 159.1 18.1
#> 10.53 15.21 15.55 13.00 17.45 16.47 20.81 16.46 7.27 12.21 15.77 10.55 15.21
#> 158 78 93 179 117 170.1 55 145 129 101.1 158.1 194.1 149.1
#> 20.14 23.88 10.33 18.63 17.46 19.54 19.34 10.07 23.41 9.97 20.14 22.40 8.37
#> 136.1 44 35 53 82 120 161 122 19 74 47 34 161.1
#> 21.83 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.1 35.1 84 98 20 47.1 191 200 95 176 31 120.1 20.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 122.1 200.1 22 122.2 1 137 28 71 74.2 122.3 142 47.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 132 103 95.1 163 137.1 143 102 146 193 38 147 31.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28.1 94 116 152 137.2 27 104 173 121 20.2 46 71.1 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.3 7 109 28.2 21 20.4 198 62 75 142.1 174 116.1 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 102.1 72 151 156 62.1 20.5 138 2 48.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[90]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0005146634 0.6931987380 0.1695818316
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.119210402 0.001849369 -0.157723063
#> grade_iii, Cure model
#> 0.770515094
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 66 22.13 1 53 0 0
#> 36 21.19 1 48 0 1
#> 39 15.59 1 37 0 1
#> 145 10.07 1 65 1 0
#> 13 14.34 1 54 0 1
#> 90 20.94 1 50 0 1
#> 166 19.98 1 48 0 0
#> 30 17.43 1 78 0 0
#> 164 23.60 1 76 0 1
#> 164.1 23.60 1 76 0 1
#> 43 12.10 1 61 0 1
#> 14 12.89 1 21 0 0
#> 169 22.41 1 46 0 0
#> 89 11.44 1 NA 0 0
#> 23 16.92 1 61 0 0
#> 113 22.86 1 34 0 0
#> 36.1 21.19 1 48 0 1
#> 189 10.51 1 NA 1 0
#> 56 12.21 1 60 0 0
#> 140 12.68 1 59 1 0
#> 88 18.37 1 47 0 0
#> 180 14.82 1 37 0 0
#> 88.1 18.37 1 47 0 0
#> 32 20.90 1 37 1 0
#> 69 23.23 1 25 0 1
#> 130 16.47 1 53 0 1
#> 184 17.77 1 38 0 0
#> 58 19.34 1 39 0 0
#> 194 22.40 1 38 0 1
#> 52 10.42 1 52 0 1
#> 57 14.46 1 45 0 1
#> 181 16.46 1 45 0 1
#> 189.1 10.51 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 36.2 21.19 1 48 0 1
#> 63 22.77 1 31 1 0
#> 164.2 23.60 1 76 0 1
#> 154 12.63 1 20 1 0
#> 181.1 16.46 1 45 0 1
#> 170 19.54 1 43 0 1
#> 37 12.52 1 57 1 0
#> 56.1 12.21 1 60 0 0
#> 36.3 21.19 1 48 0 1
#> 197 21.60 1 69 1 0
#> 149 8.37 1 33 1 0
#> 117 17.46 1 26 0 1
#> 179 18.63 1 42 0 0
#> 91 5.33 1 61 0 1
#> 181.2 16.46 1 45 0 1
#> 88.2 18.37 1 47 0 0
#> 150 20.33 1 48 0 0
#> 183 9.24 1 67 1 0
#> 29 15.45 1 68 1 0
#> 167 15.55 1 56 1 0
#> 77 7.27 1 67 0 1
#> 133 14.65 1 57 0 0
#> 117.1 17.46 1 26 0 1
#> 170.1 19.54 1 43 0 1
#> 184.1 17.77 1 38 0 0
#> 26.1 15.77 1 49 0 1
#> 52.1 10.42 1 52 0 1
#> 85 16.44 1 36 0 0
#> 180.1 14.82 1 37 0 0
#> 50 10.02 1 NA 1 0
#> 140.1 12.68 1 59 1 0
#> 177 12.53 1 75 0 0
#> 113.1 22.86 1 34 0 0
#> 170.2 19.54 1 43 0 1
#> 86 23.81 1 58 0 1
#> 57.1 14.46 1 45 0 1
#> 150.1 20.33 1 48 0 0
#> 192 16.44 1 31 1 0
#> 90.1 20.94 1 50 0 1
#> 105 19.75 1 60 0 0
#> 41 18.02 1 40 1 0
#> 149.1 8.37 1 33 1 0
#> 57.2 14.46 1 45 0 1
#> 134 17.81 1 47 1 0
#> 128 20.35 1 35 0 1
#> 123 13.00 1 44 1 0
#> 13.1 14.34 1 54 0 1
#> 190 20.81 1 42 1 0
#> 69.1 23.23 1 25 0 1
#> 88.3 18.37 1 47 0 0
#> 66.1 22.13 1 53 0 0
#> 89.1 11.44 1 NA 0 0
#> 114 13.68 1 NA 0 0
#> 30.1 17.43 1 78 0 0
#> 18 15.21 1 49 1 0
#> 129 23.41 1 53 1 0
#> 179.1 18.63 1 42 0 0
#> 36.4 21.19 1 48 0 1
#> 16 8.71 1 71 0 1
#> 4 17.64 1 NA 0 1
#> 168 23.72 1 70 0 0
#> 149.2 8.37 1 33 1 0
#> 39.1 15.59 1 37 0 1
#> 59 10.16 1 NA 1 0
#> 145.1 10.07 1 65 1 0
#> 124 9.73 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 57.3 14.46 1 45 0 1
#> 127 3.53 1 62 0 1
#> 113.2 22.86 1 34 0 0
#> 40 18.00 1 28 1 0
#> 105.1 19.75 1 60 0 0
#> 108 18.29 1 39 0 1
#> 70 7.38 1 30 1 0
#> 159 10.55 1 50 0 1
#> 26.2 15.77 1 49 0 1
#> 189.2 10.51 1 NA 1 0
#> 169.1 22.41 1 46 0 0
#> 115 24.00 0 NA 1 0
#> 176 24.00 0 43 0 1
#> 193 24.00 0 45 0 1
#> 33 24.00 0 53 0 0
#> 2 24.00 0 9 0 0
#> 147 24.00 0 76 1 0
#> 147.1 24.00 0 76 1 0
#> 200 24.00 0 64 0 0
#> 178 24.00 0 52 1 0
#> 9 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 17 24.00 0 38 0 1
#> 19 24.00 0 57 0 1
#> 118 24.00 0 44 1 0
#> 118.1 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 141 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 131 24.00 0 66 0 0
#> 46 24.00 0 71 0 0
#> 35 24.00 0 51 0 0
#> 95 24.00 0 68 0 1
#> 138 24.00 0 44 1 0
#> 116 24.00 0 58 0 1
#> 21 24.00 0 47 0 0
#> 71 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 141.1 24.00 0 44 1 0
#> 83 24.00 0 6 0 0
#> 48 24.00 0 31 1 0
#> 165.1 24.00 0 47 0 0
#> 193.1 24.00 0 45 0 1
#> 54 24.00 0 53 1 0
#> 35.1 24.00 0 51 0 0
#> 115.1 24.00 0 NA 1 0
#> 9.1 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 132.1 24.00 0 55 0 0
#> 109 24.00 0 48 0 0
#> 152 24.00 0 36 0 1
#> 21.1 24.00 0 47 0 0
#> 109.1 24.00 0 48 0 0
#> 172 24.00 0 41 0 0
#> 173 24.00 0 19 0 1
#> 12 24.00 0 63 0 0
#> 200.1 24.00 0 64 0 0
#> 109.2 24.00 0 48 0 0
#> 72 24.00 0 40 0 1
#> 120 24.00 0 68 0 1
#> 3 24.00 0 31 1 0
#> 200.2 24.00 0 64 0 0
#> 142 24.00 0 53 0 0
#> 143 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 22 24.00 0 52 1 0
#> 161 24.00 0 45 0 0
#> 196 24.00 0 19 0 0
#> 84 24.00 0 39 0 1
#> 22.1 24.00 0 52 1 0
#> 48.1 24.00 0 31 1 0
#> 176.1 24.00 0 43 0 1
#> 152.1 24.00 0 36 0 1
#> 38 24.00 0 31 1 0
#> 71.1 24.00 0 51 0 0
#> 120.1 24.00 0 68 0 1
#> 9.2 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 152.2 24.00 0 36 0 1
#> 196.1 24.00 0 19 0 0
#> 156 24.00 0 50 1 0
#> 94 24.00 0 51 0 1
#> 33.1 24.00 0 53 0 0
#> 17.1 24.00 0 38 0 1
#> 151.1 24.00 0 42 0 0
#> 33.2 24.00 0 53 0 0
#> 193.2 24.00 0 45 0 1
#> 131.1 24.00 0 66 0 0
#> 116.1 24.00 0 58 0 1
#> 35.2 24.00 0 51 0 0
#> 147.2 24.00 0 76 1 0
#> 148 24.00 0 61 1 0
#> 27 24.00 0 63 1 0
#> 146 24.00 0 63 1 0
#> 28 24.00 0 67 1 0
#> 163 24.00 0 66 0 0
#> 147.3 24.00 0 76 1 0
#> 152.3 24.00 0 36 0 1
#> 75 24.00 0 21 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.119 NA NA NA
#> 2 age, Cure model 0.00185 NA NA NA
#> 3 grade_ii, Cure model -0.158 NA NA NA
#> 4 grade_iii, Cure model 0.771 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000515 NA NA NA
#> 2 grade_ii, Survival model 0.693 NA NA NA
#> 3 grade_iii, Survival model 0.170 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.119210 0.001849 -0.157723 0.770515
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 250.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.119210402 0.001849369 -0.157723063 0.770515094
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0005146634 0.6931987380 0.1695818316
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.22560103 0.25958129 0.68830488 0.91496842 0.79158645 0.30938684
#> [7] 0.37978586 0.58006006 0.06712747 0.06712747 0.88262770 0.81698248
#> [13] 0.19103693 0.59837761 0.14411375 0.25958129 0.86643414 0.82542206
#> [19] 0.46723617 0.73217037 0.46723617 0.33014645 0.11974913 0.60761197
#> [25] 0.54336930 0.43803652 0.21393290 0.89886259 0.75792631 0.61682493
#> [31] 0.66178044 0.25958129 0.17925951 0.06712747 0.84189973 0.61682493
#> [37] 0.40930574 0.85830382 0.86643414 0.25958129 0.24839753 0.94659168
#> [43] 0.56176529 0.44783518 0.98476715 0.61682493 0.46723617 0.36022902
#> [49] 0.93081366 0.71484232 0.70602896 0.97713766 0.74930605 0.56176529
#> [55] 0.40930574 0.54336930 0.66178044 0.89886259 0.64386504 0.73217037
#> [61] 0.82542206 0.85010028 0.14411375 0.40930574 0.03039147 0.75792631
#> [67] 0.36022902 0.64386504 0.30938684 0.38969984 0.51507711 0.94659168
#> [73] 0.75792631 0.53409827 0.35032758 0.80854384 0.79158645 0.34038015
#> [79] 0.11974913 0.46723617 0.22560103 0.58006006 0.72355564 0.10639831
#> [85] 0.44783518 0.25958129 0.93870739 0.04859467 0.94659168 0.68830488
#> [91] 0.91496842 0.01096175 0.75792631 0.99238789 0.14411375 0.52467142
#> [97] 0.38969984 0.50530825 0.96949955 0.89075087 0.66178044 0.19103693
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 66 36 39 145 13 90 166 30 164 164.1 43 14 169
#> 22.13 21.19 15.59 10.07 14.34 20.94 19.98 17.43 23.60 23.60 12.10 12.89 22.41
#> 23 113 36.1 56 140 88 180 88.1 32 69 130 184 58
#> 16.92 22.86 21.19 12.21 12.68 18.37 14.82 18.37 20.90 23.23 16.47 17.77 19.34
#> 194 52 57 181 26 36.2 63 164.2 154 181.1 170 37 56.1
#> 22.40 10.42 14.46 16.46 15.77 21.19 22.77 23.60 12.63 16.46 19.54 12.52 12.21
#> 36.3 197 149 117 179 91 181.2 88.2 150 183 29 167 77
#> 21.19 21.60 8.37 17.46 18.63 5.33 16.46 18.37 20.33 9.24 15.45 15.55 7.27
#> 133 117.1 170.1 184.1 26.1 52.1 85 180.1 140.1 177 113.1 170.2 86
#> 14.65 17.46 19.54 17.77 15.77 10.42 16.44 14.82 12.68 12.53 22.86 19.54 23.81
#> 57.1 150.1 192 90.1 105 41 149.1 57.2 134 128 123 13.1 190
#> 14.46 20.33 16.44 20.94 19.75 18.02 8.37 14.46 17.81 20.35 13.00 14.34 20.81
#> 69.1 88.3 66.1 30.1 18 129 179.1 36.4 16 168 149.2 39.1 145.1
#> 23.23 18.37 22.13 17.43 15.21 23.41 18.63 21.19 8.71 23.72 8.37 15.59 10.07
#> 24 57.3 127 113.2 40 105.1 108 70 159 26.2 169.1 176 193
#> 23.89 14.46 3.53 22.86 18.00 19.75 18.29 7.38 10.55 15.77 22.41 24.00 24.00
#> 33 2 147 147.1 200 178 9 151 17 19 118 118.1 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 165 131 46 35 95 138 116 21 71 98 141.1 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 165.1 193.1 54 35.1 9.1 160 132.1 109 152 21.1 109.1 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 12 200.1 109.2 72 120 3 200.2 142 143 22 161 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 22.1 48.1 176.1 152.1 38 71.1 120.1 9.2 103 152.2 196.1 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 33.1 17.1 151.1 33.2 193.2 131.1 116.1 35.2 147.2 148 27 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 163 147.3 152.3 75
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[91]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005239915 0.436258355 -0.024375589
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.76770587 0.01334184 0.04716375
#> grade_iii, Cure model
#> 0.81824279
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 66 22.13 1 53 0 0
#> 30 17.43 1 78 0 0
#> 86 23.81 1 58 0 1
#> 58 19.34 1 39 0 0
#> 184 17.77 1 38 0 0
#> 149 8.37 1 33 1 0
#> 4 17.64 1 NA 0 1
#> 29 15.45 1 68 1 0
#> 154 12.63 1 20 1 0
#> 92 22.92 1 47 0 1
#> 189 10.51 1 NA 1 0
#> 30.1 17.43 1 78 0 0
#> 105 19.75 1 60 0 0
#> 90 20.94 1 50 0 1
#> 195 11.76 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 6 15.64 1 39 0 0
#> 60 13.15 1 38 1 0
#> 96 14.54 1 33 0 1
#> 4.1 17.64 1 NA 0 1
#> 10 10.53 1 34 0 0
#> 85 16.44 1 36 0 0
#> 199 19.81 1 NA 0 1
#> 128 20.35 1 35 0 1
#> 171 16.57 1 41 0 1
#> 100 16.07 1 60 0 0
#> 8 18.43 1 32 0 0
#> 76 19.22 1 54 0 1
#> 16 8.71 1 71 0 1
#> 197 21.60 1 69 1 0
#> 42 12.43 1 49 0 1
#> 78 23.88 1 43 0 0
#> 188 16.16 1 46 0 1
#> 40 18.00 1 28 1 0
#> 18 15.21 1 49 1 0
#> 194 22.40 1 38 0 1
#> 133 14.65 1 57 0 0
#> 195.1 11.76 1 NA 1 0
#> 189.1 10.51 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 110 17.56 1 65 0 1
#> 179 18.63 1 42 0 0
#> 6.1 15.64 1 39 0 0
#> 164 23.60 1 76 0 1
#> 136 21.83 1 43 0 1
#> 114 13.68 1 NA 0 0
#> 60.1 13.15 1 38 1 0
#> 190 20.81 1 42 1 0
#> 179.1 18.63 1 42 0 0
#> 92.1 22.92 1 47 0 1
#> 171.1 16.57 1 41 0 1
#> 155 13.08 1 26 0 0
#> 41 18.02 1 40 1 0
#> 86.1 23.81 1 58 0 1
#> 49 12.19 1 48 1 0
#> 91 5.33 1 61 0 1
#> 30.2 17.43 1 78 0 0
#> 159 10.55 1 50 0 1
#> 184.1 17.77 1 38 0 0
#> 77 7.27 1 67 0 1
#> 79 16.23 1 54 1 0
#> 171.2 16.57 1 41 0 1
#> 158 20.14 1 74 1 0
#> 92.2 22.92 1 47 0 1
#> 106 16.67 1 49 1 0
#> 170.1 19.54 1 43 0 1
#> 111 17.45 1 47 0 1
#> 86.2 23.81 1 58 0 1
#> 134 17.81 1 47 1 0
#> 130 16.47 1 53 0 1
#> 32 20.90 1 37 1 0
#> 85.1 16.44 1 36 0 0
#> 167 15.55 1 56 1 0
#> 105.1 19.75 1 60 0 0
#> 49.1 12.19 1 48 1 0
#> 93 10.33 1 52 0 1
#> 45.1 17.42 1 54 0 1
#> 190.1 20.81 1 42 1 0
#> 50 10.02 1 NA 1 0
#> 157 15.10 1 47 0 0
#> 77.1 7.27 1 67 0 1
#> 177 12.53 1 75 0 0
#> 60.2 13.15 1 38 1 0
#> 49.2 12.19 1 48 1 0
#> 108 18.29 1 39 0 1
#> 52 10.42 1 52 0 1
#> 128.1 20.35 1 35 0 1
#> 40.1 18.00 1 28 1 0
#> 168 23.72 1 70 0 0
#> 153 21.33 1 55 1 0
#> 93.1 10.33 1 52 0 1
#> 107 11.18 1 54 1 0
#> 150 20.33 1 48 0 0
#> 68 20.62 1 44 0 0
#> 66.1 22.13 1 53 0 0
#> 128.2 20.35 1 35 0 1
#> 59 10.16 1 NA 1 0
#> 111.1 17.45 1 47 0 1
#> 81 14.06 1 34 0 0
#> 40.2 18.00 1 28 1 0
#> 43 12.10 1 61 0 1
#> 15 22.68 1 48 0 0
#> 194.1 22.40 1 38 0 1
#> 93.2 10.33 1 52 0 1
#> 181 16.46 1 45 0 1
#> 42.1 12.43 1 49 0 1
#> 150.1 20.33 1 48 0 0
#> 55 19.34 1 69 0 1
#> 97 19.14 1 65 0 1
#> 150.2 20.33 1 48 0 0
#> 13 14.34 1 54 0 1
#> 79.1 16.23 1 54 1 0
#> 156 24.00 0 50 1 0
#> 131 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 80 24.00 0 41 0 0
#> 144 24.00 0 28 0 1
#> 95.1 24.00 0 68 0 1
#> 104 24.00 0 50 1 0
#> 95.2 24.00 0 68 0 1
#> 46 24.00 0 71 0 0
#> 65 24.00 0 57 1 0
#> 186 24.00 0 45 1 0
#> 196 24.00 0 19 0 0
#> 74 24.00 0 43 0 1
#> 74.1 24.00 0 43 0 1
#> 95.3 24.00 0 68 0 1
#> 82 24.00 0 34 0 0
#> 146 24.00 0 63 1 0
#> 27 24.00 0 63 1 0
#> 156.1 24.00 0 50 1 0
#> 7 24.00 0 37 1 0
#> 20 24.00 0 46 1 0
#> 172 24.00 0 41 0 0
#> 131.1 24.00 0 66 0 0
#> 172.1 24.00 0 41 0 0
#> 7.1 24.00 0 37 1 0
#> 152 24.00 0 36 0 1
#> 82.1 24.00 0 34 0 0
#> 27.1 24.00 0 63 1 0
#> 176 24.00 0 43 0 1
#> 33 24.00 0 53 0 0
#> 102 24.00 0 49 0 0
#> 143 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 196.1 24.00 0 19 0 0
#> 44 24.00 0 56 0 0
#> 176.1 24.00 0 43 0 1
#> 7.2 24.00 0 37 1 0
#> 2.1 24.00 0 9 0 0
#> 135 24.00 0 58 1 0
#> 1 24.00 0 23 1 0
#> 33.1 24.00 0 53 0 0
#> 7.3 24.00 0 37 1 0
#> 144.1 24.00 0 28 0 1
#> 172.2 24.00 0 41 0 0
#> 27.2 24.00 0 63 1 0
#> 160 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 95.4 24.00 0 68 0 1
#> 161 24.00 0 45 0 0
#> 122 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 198 24.00 0 66 0 1
#> 84 24.00 0 39 0 1
#> 142 24.00 0 53 0 0
#> 87 24.00 0 27 0 0
#> 11 24.00 0 42 0 1
#> 48 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 94 24.00 0 51 0 1
#> 122.1 24.00 0 66 0 0
#> 138 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 22 24.00 0 52 1 0
#> 122.2 24.00 0 66 0 0
#> 67 24.00 0 25 0 0
#> 11.1 24.00 0 42 0 1
#> 73 24.00 0 NA 0 1
#> 98 24.00 0 34 1 0
#> 102.1 24.00 0 49 0 0
#> 48.1 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 109 24.00 0 48 0 0
#> 119 24.00 0 17 0 0
#> 98.1 24.00 0 34 1 0
#> 161.1 24.00 0 45 0 0
#> 143.1 24.00 0 51 0 0
#> 21.1 24.00 0 47 0 0
#> 67.1 24.00 0 25 0 0
#> 94.1 24.00 0 51 0 1
#> 44.1 24.00 0 56 0 0
#> 161.2 24.00 0 45 0 0
#> 11.2 24.00 0 42 0 1
#> 75 24.00 0 21 1 0
#> 185 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 17 24.00 0 38 0 1
#> 104.1 24.00 0 50 1 0
#> 148 24.00 0 61 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.768 NA NA NA
#> 2 age, Cure model 0.0133 NA NA NA
#> 3 grade_ii, Cure model 0.0472 NA NA NA
#> 4 grade_iii, Cure model 0.818 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00524 NA NA NA
#> 2 grade_ii, Survival model 0.436 NA NA NA
#> 3 grade_iii, Survival model -0.0244 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.76771 0.01334 0.04716 0.81824
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 251.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.76770587 0.01334184 0.04716375 0.81824279
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005239915 0.436258355 -0.024375589
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.083320479 0.453724394 0.008079664 0.274256696 0.403839137 0.955864616
#> [7] 0.664115028 0.782814684 0.036941184 0.453724394 0.236287114 0.128664822
#> [13] 0.255115578 0.631816259 0.740026576 0.707303709 0.890468283 0.567868113
#> [19] 0.173463878 0.515434234 0.621046149 0.333969359 0.293741617 0.944828657
#> [25] 0.110183765 0.804394148 0.002308577 0.610326193 0.364826597 0.674908229
#> [31] 0.066672765 0.696463961 0.484206612 0.423570918 0.313841095 0.631816259
#> [37] 0.029287110 0.100825683 0.740026576 0.147194782 0.313841095 0.036941184
#> [43] 0.515434234 0.771990288 0.354570509 0.008079664 0.826017464 0.988888613
#> [49] 0.453724394 0.879626306 0.403839137 0.966862323 0.589160471 0.515434234
#> [55] 0.226884176 0.036941184 0.504980779 0.255115578 0.433626948 0.008079664
#> [61] 0.393938225 0.546558083 0.138014941 0.567868113 0.653307213 0.236287114
#> [67] 0.826017464 0.912229146 0.484206612 0.147194782 0.685667603 0.966862323
#> [73] 0.793580579 0.740026576 0.826017464 0.344238416 0.901331846 0.173463878
#> [79] 0.364826597 0.022271341 0.119481108 0.912229146 0.868817505 0.199774961
#> [85] 0.164480944 0.083320479 0.173463878 0.433626948 0.729086568 0.364826597
#> [91] 0.857986381 0.058216667 0.066672765 0.912229146 0.557189758 0.804394148
#> [97] 0.199774961 0.274256696 0.303740509 0.199774961 0.718173285 0.589160471
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 66 30 86 58 184 149 29 154 92 30.1 105 90 170
#> 22.13 17.43 23.81 19.34 17.77 8.37 15.45 12.63 22.92 17.43 19.75 20.94 19.54
#> 6 60 96 10 85 128 171 100 8 76 16 197 42
#> 15.64 13.15 14.54 10.53 16.44 20.35 16.57 16.07 18.43 19.22 8.71 21.60 12.43
#> 78 188 40 18 194 133 45 110 179 6.1 164 136 60.1
#> 23.88 16.16 18.00 15.21 22.40 14.65 17.42 17.56 18.63 15.64 23.60 21.83 13.15
#> 190 179.1 92.1 171.1 155 41 86.1 49 91 30.2 159 184.1 77
#> 20.81 18.63 22.92 16.57 13.08 18.02 23.81 12.19 5.33 17.43 10.55 17.77 7.27
#> 79 171.2 158 92.2 106 170.1 111 86.2 134 130 32 85.1 167
#> 16.23 16.57 20.14 22.92 16.67 19.54 17.45 23.81 17.81 16.47 20.90 16.44 15.55
#> 105.1 49.1 93 45.1 190.1 157 77.1 177 60.2 49.2 108 52 128.1
#> 19.75 12.19 10.33 17.42 20.81 15.10 7.27 12.53 13.15 12.19 18.29 10.42 20.35
#> 40.1 168 153 93.1 107 150 68 66.1 128.2 111.1 81 40.2 43
#> 18.00 23.72 21.33 10.33 11.18 20.33 20.62 22.13 20.35 17.45 14.06 18.00 12.10
#> 15 194.1 93.2 181 42.1 150.1 55 97 150.2 13 79.1 156 131
#> 22.68 22.40 10.33 16.46 12.43 20.33 19.34 19.14 20.33 14.34 16.23 24.00 24.00
#> 95 80 144 95.1 104 95.2 46 65 186 196 74 74.1 95.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 146 27 156.1 7 20 172 131.1 172.1 7.1 152 82.1 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 33 102 143 2 196.1 44 176.1 7.2 2.1 135 1 33.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.3 144.1 172.2 27.2 160 31 95.4 161 122 21 198 84 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 11 48 28 94 122.1 138 151 22 122.2 67 11.1 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.1 48.1 54 109 119 98.1 161.1 143.1 21.1 67.1 94.1 44.1 161.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.2 75 185 120 17 104.1 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[92]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006352723 0.367958839 0.476900797
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.05295755 0.01996096 -0.19288646
#> grade_iii, Cure model
#> 0.87500386
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 97 19.14 1 65 0 1
#> 36 21.19 1 48 0 1
#> 150 20.33 1 48 0 0
#> 58 19.34 1 39 0 0
#> 171 16.57 1 41 0 1
#> 26 15.77 1 49 0 1
#> 188 16.16 1 46 0 1
#> 16 8.71 1 71 0 1
#> 23 16.92 1 61 0 0
#> 55 19.34 1 69 0 1
#> 51 18.23 1 83 0 1
#> 6 15.64 1 39 0 0
#> 61 10.12 1 36 0 1
#> 113 22.86 1 34 0 0
#> 13 14.34 1 54 0 1
#> 184 17.77 1 38 0 0
#> 10 10.53 1 34 0 0
#> 60 13.15 1 38 1 0
#> 41 18.02 1 40 1 0
#> 111 17.45 1 47 0 1
#> 60.1 13.15 1 38 1 0
#> 167 15.55 1 56 1 0
#> 52 10.42 1 52 0 1
#> 5 16.43 1 51 0 1
#> 18 15.21 1 49 1 0
#> 96 14.54 1 33 0 1
#> 117 17.46 1 26 0 1
#> 111.1 17.45 1 47 0 1
#> 14 12.89 1 21 0 0
#> 129 23.41 1 53 1 0
#> 45 17.42 1 54 0 1
#> 99 21.19 1 38 0 1
#> 90 20.94 1 50 0 1
#> 97.1 19.14 1 65 0 1
#> 188.1 16.16 1 46 0 1
#> 6.1 15.64 1 39 0 0
#> 52.1 10.42 1 52 0 1
#> 169 22.41 1 46 0 0
#> 39 15.59 1 37 0 1
#> 150.1 20.33 1 48 0 0
#> 123 13.00 1 44 1 0
#> 166 19.98 1 48 0 0
#> 127 3.53 1 62 0 1
#> 171.1 16.57 1 41 0 1
#> 29 15.45 1 68 1 0
#> 77 7.27 1 67 0 1
#> 149 8.37 1 33 1 0
#> 128 20.35 1 35 0 1
#> 190 20.81 1 42 1 0
#> 195 11.76 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 168 23.72 1 70 0 0
#> 100 16.07 1 60 0 0
#> 183 9.24 1 67 1 0
#> 125 15.65 1 67 1 0
#> 166.1 19.98 1 48 0 0
#> 154 12.63 1 20 1 0
#> 29.1 15.45 1 68 1 0
#> 181 16.46 1 45 0 1
#> 8 18.43 1 32 0 0
#> 26.1 15.77 1 49 0 1
#> 89 11.44 1 NA 0 0
#> 140 12.68 1 59 1 0
#> 111.2 17.45 1 47 0 1
#> 166.2 19.98 1 48 0 0
#> 59 10.16 1 NA 1 0
#> 171.2 16.57 1 41 0 1
#> 100.1 16.07 1 60 0 0
#> 97.2 19.14 1 65 0 1
#> 5.1 16.43 1 51 0 1
#> 77.1 7.27 1 67 0 1
#> 197 21.60 1 69 1 0
#> 81 14.06 1 34 0 0
#> 43 12.10 1 61 0 1
#> 181.1 16.46 1 45 0 1
#> 111.3 17.45 1 47 0 1
#> 108 18.29 1 39 0 1
#> 10.1 10.53 1 34 0 0
#> 127.1 3.53 1 62 0 1
#> 16.1 8.71 1 71 0 1
#> 26.2 15.77 1 49 0 1
#> 30 17.43 1 78 0 0
#> 89.1 11.44 1 NA 0 0
#> 99.1 21.19 1 38 0 1
#> 134 17.81 1 47 1 0
#> 158 20.14 1 74 1 0
#> 117.1 17.46 1 26 0 1
#> 30.1 17.43 1 78 0 0
#> 108.1 18.29 1 39 0 1
#> 167.1 15.55 1 56 1 0
#> 63 22.77 1 31 1 0
#> 39.1 15.59 1 37 0 1
#> 76 19.22 1 54 0 1
#> 30.2 17.43 1 78 0 0
#> 30.3 17.43 1 78 0 0
#> 40 18.00 1 28 1 0
#> 43.1 12.10 1 61 0 1
#> 114 13.68 1 NA 0 0
#> 183.1 9.24 1 67 1 0
#> 93 10.33 1 52 0 1
#> 159 10.55 1 50 0 1
#> 101 9.97 1 10 0 1
#> 49 12.19 1 48 1 0
#> 150.2 20.33 1 48 0 0
#> 16.2 8.71 1 71 0 1
#> 134.1 17.81 1 47 1 0
#> 114.1 13.68 1 NA 0 0
#> 199 19.81 1 NA 0 1
#> 56 12.21 1 60 0 0
#> 89.2 11.44 1 NA 0 0
#> 26.3 15.77 1 49 0 1
#> 60.2 13.15 1 38 1 0
#> 191 24.00 0 60 0 1
#> 161 24.00 0 45 0 0
#> 87 24.00 0 27 0 0
#> 98 24.00 0 34 1 0
#> 1 24.00 0 23 1 0
#> 20 24.00 0 46 1 0
#> 54 24.00 0 53 1 0
#> 120 24.00 0 68 0 1
#> 75 24.00 0 21 1 0
#> 22 24.00 0 52 1 0
#> 34 24.00 0 36 0 0
#> 141 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 148 24.00 0 61 1 0
#> 118 24.00 0 44 1 0
#> 172 24.00 0 41 0 0
#> 34.1 24.00 0 36 0 0
#> 103 24.00 0 56 1 0
#> 152 24.00 0 36 0 1
#> 178 24.00 0 52 1 0
#> 148.1 24.00 0 61 1 0
#> 75.1 24.00 0 21 1 0
#> 48 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 46 24.00 0 71 0 0
#> 84 24.00 0 39 0 1
#> 87.1 24.00 0 27 0 0
#> 31 24.00 0 36 0 1
#> 35 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 165 24.00 0 47 0 0
#> 152.1 24.00 0 36 0 1
#> 135 24.00 0 58 1 0
#> 64 24.00 0 43 0 0
#> 12 24.00 0 63 0 0
#> 84.1 24.00 0 39 0 1
#> 152.2 24.00 0 36 0 1
#> 7 24.00 0 37 1 0
#> 193 24.00 0 45 0 1
#> 83 24.00 0 6 0 0
#> 119 24.00 0 17 0 0
#> 35.1 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 94 24.00 0 51 0 1
#> 65 24.00 0 57 1 0
#> 64.1 24.00 0 43 0 0
#> 161.1 24.00 0 45 0 0
#> 2 24.00 0 9 0 0
#> 83.1 24.00 0 6 0 0
#> 12.1 24.00 0 63 0 0
#> 1.1 24.00 0 23 1 0
#> 116 24.00 0 58 0 1
#> 35.2 24.00 0 51 0 0
#> 131 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 11 24.00 0 42 0 1
#> 193.1 24.00 0 45 0 1
#> 95 24.00 0 68 0 1
#> 2.1 24.00 0 9 0 0
#> 103.1 24.00 0 56 1 0
#> 17 24.00 0 38 0 1
#> 103.2 24.00 0 56 1 0
#> 191.1 24.00 0 60 0 1
#> 21 24.00 0 47 0 0
#> 31.1 24.00 0 36 0 1
#> 48.1 24.00 0 31 1 0
#> 83.2 24.00 0 6 0 0
#> 198 24.00 0 66 0 1
#> 74 24.00 0 43 0 1
#> 95.1 24.00 0 68 0 1
#> 27 24.00 0 63 1 0
#> 1.2 24.00 0 23 1 0
#> 198.1 24.00 0 66 0 1
#> 138 24.00 0 44 1 0
#> 98.1 24.00 0 34 1 0
#> 185 24.00 0 44 1 0
#> 135.1 24.00 0 58 1 0
#> 137 24.00 0 45 1 0
#> 47 24.00 0 38 0 1
#> 48.2 24.00 0 31 1 0
#> 95.2 24.00 0 68 0 1
#> 174 24.00 0 49 1 0
#> 31.2 24.00 0 36 0 1
#> 103.3 24.00 0 56 1 0
#> 151 24.00 0 42 0 0
#> 112 24.00 0 61 0 0
#> 126 24.00 0 48 0 0
#> 48.3 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.05 NA NA NA
#> 2 age, Cure model 0.0200 NA NA NA
#> 3 grade_ii, Cure model -0.193 NA NA NA
#> 4 grade_iii, Cure model 0.875 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00635 NA NA NA
#> 2 grade_ii, Survival model 0.368 NA NA NA
#> 3 grade_iii, Survival model 0.477 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.05296 0.01996 -0.19289 0.87500
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 249.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.05295755 0.01996096 -0.19288646 0.87500386
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006352723 0.367958839 0.476900797
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.45924754 0.25269135 0.34031941 0.42558446 0.66425724 0.74032521
#> [7] 0.71356920 0.96003802 0.65674233 0.42558446 0.51763873 0.77199003
#> [13] 0.93908087 0.16081480 0.83294515 0.56241169 0.91219327 0.84465851
#> [19] 0.52690890 0.58794060 0.84465851 0.79694604 0.92305113 0.69983469
#> [25] 0.82107414 0.82703066 0.57111832 0.58794060 0.86751151 0.10133232
#> [31] 0.64918650 0.25269135 0.29760322 0.45924754 0.71356920 0.77199003
#> [37] 0.92305113 0.21003285 0.78457102 0.34031941 0.86179560 0.39053103
#> [43] 0.99019572 0.66425724 0.80912029 0.98025475 0.97519621 0.32668149
#> [49] 0.31244203 0.13395303 0.05337715 0.72700431 0.94965439 0.76564451
#> [55] 0.39053103 0.87889175 0.80912029 0.68576116 0.48870527 0.74032521
#> [61] 0.87322206 0.58794060 0.39053103 0.66425724 0.72700431 0.45924754
#> [67] 0.69983469 0.98025475 0.23256909 0.83880676 0.89576353 0.68576116
#> [73] 0.58794060 0.49868257 0.91219327 0.99019572 0.96003802 0.74032521
#> [79] 0.61904894 0.25269135 0.54506047 0.37806781 0.57111832 0.61904894
#> [85] 0.49868257 0.79694604 0.18664836 0.78457102 0.44816865 0.61904894
#> [91] 0.61904894 0.53604046 0.89576353 0.94965439 0.93375269 0.90673236
#> [97] 0.94437824 0.89016781 0.34031941 0.96003802 0.54506047 0.88453812
#> [103] 0.74032521 0.84465851 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 97 36 150 58 171 26 188 16 23 55 51 6 61
#> 19.14 21.19 20.33 19.34 16.57 15.77 16.16 8.71 16.92 19.34 18.23 15.64 10.12
#> 113 13 184 10 60 41 111 60.1 167 52 5 18 96
#> 22.86 14.34 17.77 10.53 13.15 18.02 17.45 13.15 15.55 10.42 16.43 15.21 14.54
#> 117 111.1 14 129 45 99 90 97.1 188.1 6.1 52.1 169 39
#> 17.46 17.45 12.89 23.41 17.42 21.19 20.94 19.14 16.16 15.64 10.42 22.41 15.59
#> 150.1 123 166 127 171.1 29 77 149 128 190 69 168 100
#> 20.33 13.00 19.98 3.53 16.57 15.45 7.27 8.37 20.35 20.81 23.23 23.72 16.07
#> 183 125 166.1 154 29.1 181 8 26.1 140 111.2 166.2 171.2 100.1
#> 9.24 15.65 19.98 12.63 15.45 16.46 18.43 15.77 12.68 17.45 19.98 16.57 16.07
#> 97.2 5.1 77.1 197 81 43 181.1 111.3 108 10.1 127.1 16.1 26.2
#> 19.14 16.43 7.27 21.60 14.06 12.10 16.46 17.45 18.29 10.53 3.53 8.71 15.77
#> 30 99.1 134 158 117.1 30.1 108.1 167.1 63 39.1 76 30.2 30.3
#> 17.43 21.19 17.81 20.14 17.46 17.43 18.29 15.55 22.77 15.59 19.22 17.43 17.43
#> 40 43.1 183.1 93 159 101 49 150.2 16.2 134.1 56 26.3 60.2
#> 18.00 12.10 9.24 10.33 10.55 9.97 12.19 20.33 8.71 17.81 12.21 15.77 13.15
#> 191 161 87 98 1 20 54 120 75 22 34 141 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 118 172 34.1 103 152 178 148.1 75.1 48 80 46 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1 31 35 156 165 152.1 135 64 12 84.1 152.2 7 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 119 35.1 62 94 65 64.1 161.1 2 83.1 12.1 1.1 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.2 131 146 11 193.1 95 2.1 103.1 17 103.2 191.1 21 31.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.1 83.2 198 74 95.1 27 1.2 198.1 138 98.1 185 135.1 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 48.2 95.2 174 31.2 103.3 151 112 126 48.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[93]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002326277 0.373837713 0.604250892
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.89694878 0.01977144 0.26910661
#> grade_iii, Cure model
#> 0.29142172
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 13 14.34 1 54 0 1
#> 184 17.77 1 38 0 0
#> 124 9.73 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 42 12.43 1 49 0 1
#> 55 19.34 1 69 0 1
#> 32 20.90 1 37 1 0
#> 15 22.68 1 48 0 0
#> 149 8.37 1 33 1 0
#> 14 12.89 1 21 0 0
#> 139 21.49 1 63 1 0
#> 78 23.88 1 43 0 0
#> 114 13.68 1 NA 0 0
#> 69 23.23 1 25 0 1
#> 149.1 8.37 1 33 1 0
#> 60 13.15 1 38 1 0
#> 125 15.65 1 67 1 0
#> 127 3.53 1 62 0 1
#> 59 10.16 1 NA 1 0
#> 197 21.60 1 69 1 0
#> 10 10.53 1 34 0 0
#> 52 10.42 1 52 0 1
#> 150 20.33 1 48 0 0
#> 36 21.19 1 48 0 1
#> 149.2 8.37 1 33 1 0
#> 128 20.35 1 35 0 1
#> 77 7.27 1 67 0 1
#> 90 20.94 1 50 0 1
#> 153 21.33 1 55 1 0
#> 184.1 17.77 1 38 0 0
#> 43 12.10 1 61 0 1
#> 16 8.71 1 71 0 1
#> 181 16.46 1 45 0 1
#> 179 18.63 1 42 0 0
#> 99 21.19 1 38 0 1
#> 57 14.46 1 45 0 1
#> 42.1 12.43 1 49 0 1
#> 105 19.75 1 60 0 0
#> 166 19.98 1 48 0 0
#> 61 10.12 1 36 0 1
#> 139.1 21.49 1 63 1 0
#> 52.1 10.42 1 52 0 1
#> 170 19.54 1 43 0 1
#> 117 17.46 1 26 0 1
#> 85 16.44 1 36 0 0
#> 150.1 20.33 1 48 0 0
#> 149.3 8.37 1 33 1 0
#> 89 11.44 1 NA 0 0
#> 159 10.55 1 50 0 1
#> 187 9.92 1 39 1 0
#> 113 22.86 1 34 0 0
#> 93 10.33 1 52 0 1
#> 106 16.67 1 49 1 0
#> 99.1 21.19 1 38 0 1
#> 88 18.37 1 47 0 0
#> 14.1 12.89 1 21 0 0
#> 63 22.77 1 31 1 0
#> 24 23.89 1 38 0 0
#> 123 13.00 1 44 1 0
#> 93.1 10.33 1 52 0 1
#> 154 12.63 1 20 1 0
#> 154.1 12.63 1 20 1 0
#> 123.1 13.00 1 44 1 0
#> 51 18.23 1 83 0 1
#> 127.1 3.53 1 62 0 1
#> 79 16.23 1 54 1 0
#> 58 19.34 1 39 0 0
#> 91 5.33 1 61 0 1
#> 30 17.43 1 78 0 0
#> 128.1 20.35 1 35 0 1
#> 155 13.08 1 26 0 0
#> 159.1 10.55 1 50 0 1
#> 32.1 20.90 1 37 1 0
#> 153.1 21.33 1 55 1 0
#> 88.1 18.37 1 47 0 0
#> 139.2 21.49 1 63 1 0
#> 195 11.76 1 NA 1 0
#> 106.1 16.67 1 49 1 0
#> 49 12.19 1 48 1 0
#> 25 6.32 1 34 1 0
#> 145 10.07 1 65 1 0
#> 70 7.38 1 30 1 0
#> 88.2 18.37 1 47 0 0
#> 110 17.56 1 65 0 1
#> 197.1 21.60 1 69 1 0
#> 23 16.92 1 61 0 0
#> 37.1 12.52 1 57 1 0
#> 180 14.82 1 37 0 0
#> 124.1 9.73 1 NA 1 0
#> 145.1 10.07 1 65 1 0
#> 106.2 16.67 1 49 1 0
#> 30.1 17.43 1 78 0 0
#> 106.3 16.67 1 49 1 0
#> 171 16.57 1 41 0 1
#> 159.2 10.55 1 50 0 1
#> 79.1 16.23 1 54 1 0
#> 167 15.55 1 56 1 0
#> 199 19.81 1 NA 0 1
#> 153.2 21.33 1 55 1 0
#> 88.3 18.37 1 47 0 0
#> 40 18.00 1 28 1 0
#> 189 10.51 1 NA 1 0
#> 14.2 12.89 1 21 0 0
#> 101 9.97 1 10 0 1
#> 30.2 17.43 1 78 0 0
#> 97 19.14 1 65 0 1
#> 68 20.62 1 44 0 0
#> 61.1 10.12 1 36 0 1
#> 61.2 10.12 1 36 0 1
#> 90.1 20.94 1 50 0 1
#> 61.3 10.12 1 36 0 1
#> 117.1 17.46 1 26 0 1
#> 119 24.00 0 17 0 0
#> 62 24.00 0 71 0 0
#> 146 24.00 0 63 1 0
#> 3 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 3.1 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 174 24.00 0 49 1 0
#> 160 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 53 24.00 0 32 0 1
#> 31 24.00 0 36 0 1
#> 83 24.00 0 6 0 0
#> 9 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 1 24.00 0 23 1 0
#> 152.1 24.00 0 36 0 1
#> 11 24.00 0 42 0 1
#> 73 24.00 0 NA 0 1
#> 33 24.00 0 53 0 0
#> 116 24.00 0 58 0 1
#> 12 24.00 0 63 0 0
#> 200 24.00 0 64 0 0
#> 121 24.00 0 57 1 0
#> 173 24.00 0 19 0 1
#> 141 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 1.1 24.00 0 23 1 0
#> 47 24.00 0 38 0 1
#> 144 24.00 0 28 0 1
#> 141.1 24.00 0 44 1 0
#> 2 24.00 0 9 0 0
#> 120 24.00 0 68 0 1
#> 47.1 24.00 0 38 0 1
#> 31.1 24.00 0 36 0 1
#> 71 24.00 0 51 0 0
#> 83.1 24.00 0 6 0 0
#> 126 24.00 0 48 0 0
#> 75 24.00 0 21 1 0
#> 53.1 24.00 0 32 0 1
#> 80 24.00 0 41 0 0
#> 3.2 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 165 24.00 0 47 0 0
#> 95 24.00 0 68 0 1
#> 112 24.00 0 61 0 0
#> 19 24.00 0 57 0 1
#> 3.3 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 163 24.00 0 66 0 0
#> 9.1 24.00 0 31 1 0
#> 47.2 24.00 0 38 0 1
#> 173.1 24.00 0 19 0 1
#> 173.2 24.00 0 19 0 1
#> 143 24.00 0 51 0 0
#> 3.4 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 75.1 24.00 0 21 1 0
#> 47.3 24.00 0 38 0 1
#> 19.1 24.00 0 57 0 1
#> 161 24.00 0 45 0 0
#> 109 24.00 0 48 0 0
#> 27 24.00 0 63 1 0
#> 54 24.00 0 53 1 0
#> 141.2 24.00 0 44 1 0
#> 21.1 24.00 0 47 0 0
#> 74 24.00 0 43 0 1
#> 112.1 24.00 0 61 0 0
#> 162 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 83.2 24.00 0 6 0 0
#> 11.1 24.00 0 42 0 1
#> 87 24.00 0 27 0 0
#> 121.1 24.00 0 57 1 0
#> 116.1 24.00 0 58 0 1
#> 83.3 24.00 0 6 0 0
#> 1.2 24.00 0 23 1 0
#> 138 24.00 0 44 1 0
#> 174.1 24.00 0 49 1 0
#> 35 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 20 24.00 0 46 1 0
#> 132 24.00 0 55 0 0
#> 144.1 24.00 0 28 0 1
#> 198 24.00 0 66 0 1
#> 163.1 24.00 0 66 0 0
#> 176 24.00 0 43 0 1
#> 95.1 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.897 NA NA NA
#> 2 age, Cure model 0.0198 NA NA NA
#> 3 grade_ii, Cure model 0.269 NA NA NA
#> 4 grade_iii, Cure model 0.291 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00233 NA NA NA
#> 2 grade_ii, Survival model 0.374 NA NA NA
#> 3 grade_iii, Survival model 0.604 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.89695 0.01977 0.26911 0.29142
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 258 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.89694878 0.01977144 0.26910661 0.29142172
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002326277 0.373837713 0.604250892
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.661439343 0.464534490 0.746002799 0.762659510 0.369965990 0.270598731
#> [7] 0.100128527 0.926748702 0.704027774 0.144443563 0.029361846 0.050860386
#> [13] 0.926748702 0.670029612 0.626563255 0.985540999 0.116201576 0.819340944
#> [19] 0.827370956 0.320637789 0.217680693 0.926748702 0.301200954 0.963499713
#> [25] 0.249825387 0.182071678 0.464534490 0.787321654 0.919239607 0.591398551
#> [31] 0.398651340 0.217680693 0.652780041 0.762659510 0.350156985 0.340200242
#> [37] 0.858774366 0.144443563 0.827370956 0.360150766 0.492712122 0.600249578
#> [43] 0.320637789 0.926748702 0.795503824 0.911696544 0.067426384 0.843163500
#> [49] 0.547173616 0.217680693 0.408224038 0.704027774 0.084328274 0.009848042
#> [55] 0.687144030 0.843163500 0.729244019 0.729244019 0.687144030 0.445540971
#> [61] 0.985540999 0.609111104 0.369965990 0.978221835 0.510808754 0.301200954
#> [67] 0.678583654 0.795503824 0.270598731 0.182071678 0.408224038 0.144443563
#> [73] 0.547173616 0.779089197 0.970870339 0.888969679 0.956097047 0.408224038
#> [79] 0.483327859 0.116201576 0.537949321 0.746002799 0.644045661 0.888969679
#> [85] 0.547173616 0.510808754 0.547173616 0.582460848 0.795503824 0.609111104
#> [91] 0.635321041 0.182071678 0.408224038 0.455073562 0.704027774 0.904133001
#> [97] 0.510808754 0.389100001 0.290854564 0.858774366 0.858774366 0.249825387
#> [103] 0.858774366 0.492712122 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 13 184 37 42 55 32 15 149 14 139 78 69 149.1
#> 14.34 17.77 12.52 12.43 19.34 20.90 22.68 8.37 12.89 21.49 23.88 23.23 8.37
#> 60 125 127 197 10 52 150 36 149.2 128 77 90 153
#> 13.15 15.65 3.53 21.60 10.53 10.42 20.33 21.19 8.37 20.35 7.27 20.94 21.33
#> 184.1 43 16 181 179 99 57 42.1 105 166 61 139.1 52.1
#> 17.77 12.10 8.71 16.46 18.63 21.19 14.46 12.43 19.75 19.98 10.12 21.49 10.42
#> 170 117 85 150.1 149.3 159 187 113 93 106 99.1 88 14.1
#> 19.54 17.46 16.44 20.33 8.37 10.55 9.92 22.86 10.33 16.67 21.19 18.37 12.89
#> 63 24 123 93.1 154 154.1 123.1 51 127.1 79 58 91 30
#> 22.77 23.89 13.00 10.33 12.63 12.63 13.00 18.23 3.53 16.23 19.34 5.33 17.43
#> 128.1 155 159.1 32.1 153.1 88.1 139.2 106.1 49 25 145 70 88.2
#> 20.35 13.08 10.55 20.90 21.33 18.37 21.49 16.67 12.19 6.32 10.07 7.38 18.37
#> 110 197.1 23 37.1 180 145.1 106.2 30.1 106.3 171 159.2 79.1 167
#> 17.56 21.60 16.92 12.52 14.82 10.07 16.67 17.43 16.67 16.57 10.55 16.23 15.55
#> 153.2 88.3 40 14.2 101 30.2 97 68 61.1 61.2 90.1 61.3 117.1
#> 21.33 18.37 18.00 12.89 9.97 17.43 19.14 20.62 10.12 10.12 20.94 10.12 17.46
#> 119 62 146 3 21 3.1 152 174 160 65 53 31 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 191 1 152.1 11 33 116 12 200 121 173 141 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.1 47 144 141.1 2 120 47.1 31.1 71 83.1 126 75 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 3.2 193 165 95 112 19 3.3 67 163 9.1 47.2 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173.2 143 3.4 104 75.1 47.3 19.1 161 109 27 54 141.2 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 112.1 162 103 83.2 11.1 87 121.1 116.1 83.3 1.2 138 174.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 151 20 132 144.1 198 163.1 176 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[94]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009607467 0.975756162 0.411323706
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.49817969 -0.01249189 0.13458413
#> grade_iii, Cure model
#> 0.62922589
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 49 12.19 1 48 1 0
#> 79 16.23 1 54 1 0
#> 88 18.37 1 47 0 0
#> 114 13.68 1 NA 0 0
#> 177 12.53 1 75 0 0
#> 140 12.68 1 59 1 0
#> 106 16.67 1 49 1 0
#> 107 11.18 1 54 1 0
#> 70 7.38 1 30 1 0
#> 150 20.33 1 48 0 0
#> 175 21.91 1 43 0 0
#> 170 19.54 1 43 0 1
#> 113 22.86 1 34 0 0
#> 58 19.34 1 39 0 0
#> 154 12.63 1 20 1 0
#> 76 19.22 1 54 0 1
#> 108 18.29 1 39 0 1
#> 117 17.46 1 26 0 1
#> 136 21.83 1 43 0 1
#> 111 17.45 1 47 0 1
#> 92 22.92 1 47 0 1
#> 166 19.98 1 48 0 0
#> 89 11.44 1 NA 0 0
#> 105 19.75 1 60 0 0
#> 170.1 19.54 1 43 0 1
#> 13 14.34 1 54 0 1
#> 99 21.19 1 38 0 1
#> 69 23.23 1 25 0 1
#> 6 15.64 1 39 0 0
#> 168 23.72 1 70 0 0
#> 68 20.62 1 44 0 0
#> 111.1 17.45 1 47 0 1
#> 78 23.88 1 43 0 0
#> 85 16.44 1 36 0 0
#> 123 13.00 1 44 1 0
#> 15 22.68 1 48 0 0
#> 79.1 16.23 1 54 1 0
#> 99.1 21.19 1 38 0 1
#> 96 14.54 1 33 0 1
#> 154.1 12.63 1 20 1 0
#> 157 15.10 1 47 0 0
#> 177.1 12.53 1 75 0 0
#> 110 17.56 1 65 0 1
#> 101 9.97 1 10 0 1
#> 61 10.12 1 36 0 1
#> 134 17.81 1 47 1 0
#> 45 17.42 1 54 0 1
#> 16 8.71 1 71 0 1
#> 14 12.89 1 21 0 0
#> 166.1 19.98 1 48 0 0
#> 81 14.06 1 34 0 0
#> 105.1 19.75 1 60 0 0
#> 155 13.08 1 26 0 0
#> 45.1 17.42 1 54 0 1
#> 188 16.16 1 46 0 1
#> 159 10.55 1 50 0 1
#> 69.1 23.23 1 25 0 1
#> 30 17.43 1 78 0 0
#> 5 16.43 1 51 0 1
#> 169 22.41 1 46 0 0
#> 189 10.51 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 168.1 23.72 1 70 0 0
#> 187 9.92 1 39 1 0
#> 26 15.77 1 49 0 1
#> 61.1 10.12 1 36 0 1
#> 32 20.90 1 37 1 0
#> 39 15.59 1 37 0 1
#> 8 18.43 1 32 0 0
#> 157.1 15.10 1 47 0 0
#> 189.1 10.51 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 168.2 23.72 1 70 0 0
#> 50 10.02 1 NA 1 0
#> 89.1 11.44 1 NA 0 0
#> 150.1 20.33 1 48 0 0
#> 18 15.21 1 49 1 0
#> 88.1 18.37 1 47 0 0
#> 69.2 23.23 1 25 0 1
#> 111.2 17.45 1 47 0 1
#> 26.1 15.77 1 49 0 1
#> 111.3 17.45 1 47 0 1
#> 32.1 20.90 1 37 1 0
#> 92.1 22.92 1 47 0 1
#> 117.1 17.46 1 26 0 1
#> 6.1 15.64 1 39 0 0
#> 129 23.41 1 53 1 0
#> 76.1 19.22 1 54 0 1
#> 189.2 10.51 1 NA 1 0
#> 99.2 21.19 1 38 0 1
#> 199 19.81 1 NA 0 1
#> 128 20.35 1 35 0 1
#> 101.1 9.97 1 10 0 1
#> 68.1 20.62 1 44 0 0
#> 42 12.43 1 49 0 1
#> 114.1 13.68 1 NA 0 0
#> 6.2 15.64 1 39 0 0
#> 105.2 19.75 1 60 0 0
#> 101.2 9.97 1 10 0 1
#> 96.1 14.54 1 33 0 1
#> 57 14.46 1 45 0 1
#> 111.4 17.45 1 47 0 1
#> 149 8.37 1 33 1 0
#> 175.1 21.91 1 43 0 0
#> 24 23.89 1 38 0 0
#> 5.1 16.43 1 51 0 1
#> 111.5 17.45 1 47 0 1
#> 179 18.63 1 42 0 0
#> 39.1 15.59 1 37 0 1
#> 158 20.14 1 74 1 0
#> 164 23.60 1 76 0 1
#> 167 15.55 1 56 1 0
#> 161 24.00 0 45 0 0
#> 112 24.00 0 61 0 0
#> 174 24.00 0 49 1 0
#> 116 24.00 0 58 0 1
#> 198 24.00 0 66 0 1
#> 163 24.00 0 66 0 0
#> 11 24.00 0 42 0 1
#> 172 24.00 0 41 0 0
#> 116.1 24.00 0 58 0 1
#> 47 24.00 0 38 0 1
#> 148 24.00 0 61 1 0
#> 22 24.00 0 52 1 0
#> 198.1 24.00 0 66 0 1
#> 121 24.00 0 57 1 0
#> 193 24.00 0 45 0 1
#> 176 24.00 0 43 0 1
#> 162 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 122 24.00 0 66 0 0
#> 156 24.00 0 50 1 0
#> 17 24.00 0 38 0 1
#> 7 24.00 0 37 1 0
#> 2 24.00 0 9 0 0
#> 11.1 24.00 0 42 0 1
#> 131 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#> 152 24.00 0 36 0 1
#> 137 24.00 0 45 1 0
#> 46 24.00 0 71 0 0
#> 198.2 24.00 0 66 0 1
#> 186 24.00 0 45 1 0
#> 82 24.00 0 34 0 0
#> 2.1 24.00 0 9 0 0
#> 196 24.00 0 19 0 0
#> 148.1 24.00 0 61 1 0
#> 151 24.00 0 42 0 0
#> 131.1 24.00 0 66 0 0
#> 7.1 24.00 0 37 1 0
#> 142 24.00 0 53 0 0
#> 143 24.00 0 51 0 0
#> 198.3 24.00 0 66 0 1
#> 172.1 24.00 0 41 0 0
#> 132.1 24.00 0 55 0 0
#> 65 24.00 0 57 1 0
#> 72 24.00 0 40 0 1
#> 64 24.00 0 43 0 0
#> 75 24.00 0 21 1 0
#> 12 24.00 0 63 0 0
#> 191.1 24.00 0 60 0 1
#> 151.1 24.00 0 42 0 0
#> 146 24.00 0 63 1 0
#> 163.1 24.00 0 66 0 0
#> 12.1 24.00 0 63 0 0
#> 35 24.00 0 51 0 0
#> 47.1 24.00 0 38 0 1
#> 75.1 24.00 0 21 1 0
#> 17.1 24.00 0 38 0 1
#> 47.2 24.00 0 38 0 1
#> 75.2 24.00 0 21 1 0
#> 62 24.00 0 71 0 0
#> 151.2 24.00 0 42 0 0
#> 146.1 24.00 0 63 1 0
#> 64.1 24.00 0 43 0 0
#> 116.2 24.00 0 58 0 1
#> 160 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 35.1 24.00 0 51 0 0
#> 46.1 24.00 0 71 0 0
#> 115 24.00 0 NA 1 0
#> 22.1 24.00 0 52 1 0
#> 7.2 24.00 0 37 1 0
#> 71 24.00 0 51 0 0
#> 144 24.00 0 28 0 1
#> 19 24.00 0 57 0 1
#> 31 24.00 0 36 0 1
#> 182 24.00 0 35 0 0
#> 200 24.00 0 64 0 0
#> 44 24.00 0 56 0 0
#> 115.1 24.00 0 NA 1 0
#> 102 24.00 0 49 0 0
#> 84 24.00 0 39 0 1
#> 147 24.00 0 76 1 0
#> 67.1 24.00 0 25 0 0
#> 84.1 24.00 0 39 0 1
#> 62.1 24.00 0 71 0 0
#> 172.2 24.00 0 41 0 0
#> 67.2 24.00 0 25 0 0
#> 116.3 24.00 0 58 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.498 NA NA NA
#> 2 age, Cure model -0.0125 NA NA NA
#> 3 grade_ii, Cure model 0.135 NA NA NA
#> 4 grade_iii, Cure model 0.629 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00961 NA NA NA
#> 2 grade_ii, Survival model 0.976 NA NA NA
#> 3 grade_iii, Survival model 0.411 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.49818 -0.01249 0.13458 0.62923
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 254.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.49817969 -0.01249189 0.13458413 0.62922589
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009607467 0.975756162 0.411323706
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.874282051 0.579516975 0.375250338 0.834413472 0.804518654 0.538088185
#> [7] 0.884176414 0.990570478 0.228385873 0.126130457 0.304513570 0.098277672
#> [13] 0.324304585 0.814720457 0.334454174 0.396137199 0.427537882 0.145488689
#> [19] 0.447986639 0.081507791 0.256391436 0.275318758 0.304513570 0.753077802
#> [25] 0.155514672 0.057891006 0.630303012 0.012816254 0.201042328 0.447986639
#> [31] 0.006129414 0.548436316 0.784007699 0.107278938 0.579516975 0.155514672
#> [37] 0.722446061 0.814720457 0.702017163 0.834413472 0.417099741 0.933163438
#> [43] 0.903844914 0.406711519 0.517331246 0.971445339 0.794251079 0.256391436
#> [49] 0.763351822 0.275318758 0.773664522 0.517331246 0.599773591 0.894007055
#> [55] 0.057891006 0.506889715 0.558841859 0.116568463 0.854348096 0.012816254
#> [61] 0.961861805 0.609994145 0.903844914 0.183470025 0.660979352 0.364870469
#> [67] 0.702017163 0.923384954 0.012816254 0.228385873 0.691835773 0.375250338
#> [73] 0.057891006 0.447986639 0.609994145 0.447986639 0.183470025 0.081507791
#> [79] 0.427537882 0.630303012 0.047778082 0.334454174 0.155514672 0.219161287
#> [85] 0.933163438 0.201042328 0.864311757 0.630303012 0.275318758 0.933163438
#> [91] 0.722446061 0.742818048 0.447986639 0.981051356 0.126130457 0.001451307
#> [97] 0.558841859 0.447986639 0.354568185 0.660979352 0.247007487 0.036229106
#> [103] 0.681554990 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 49 79 88 177 140 106 107 70 150 175 170 113 58
#> 12.19 16.23 18.37 12.53 12.68 16.67 11.18 7.38 20.33 21.91 19.54 22.86 19.34
#> 154 76 108 117 136 111 92 166 105 170.1 13 99 69
#> 12.63 19.22 18.29 17.46 21.83 17.45 22.92 19.98 19.75 19.54 14.34 21.19 23.23
#> 6 168 68 111.1 78 85 123 15 79.1 99.1 96 154.1 157
#> 15.64 23.72 20.62 17.45 23.88 16.44 13.00 22.68 16.23 21.19 14.54 12.63 15.10
#> 177.1 110 101 61 134 45 16 14 166.1 81 105.1 155 45.1
#> 12.53 17.56 9.97 10.12 17.81 17.42 8.71 12.89 19.98 14.06 19.75 13.08 17.42
#> 188 159 69.1 30 5 169 37 168.1 187 26 61.1 32 39
#> 16.16 10.55 23.23 17.43 16.43 22.41 12.52 23.72 9.92 15.77 10.12 20.90 15.59
#> 8 157.1 145 168.2 150.1 18 88.1 69.2 111.2 26.1 111.3 32.1 92.1
#> 18.43 15.10 10.07 23.72 20.33 15.21 18.37 23.23 17.45 15.77 17.45 20.90 22.92
#> 117.1 6.1 129 76.1 99.2 128 101.1 68.1 42 6.2 105.2 101.2 96.1
#> 17.46 15.64 23.41 19.22 21.19 20.35 9.97 20.62 12.43 15.64 19.75 9.97 14.54
#> 57 111.4 149 175.1 24 5.1 111.5 179 39.1 158 164 167 161
#> 14.46 17.45 8.37 21.91 23.89 16.43 17.45 18.63 15.59 20.14 23.60 15.55 24.00
#> 112 174 116 198 163 11 172 116.1 47 148 22 198.1 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 176 162 191 122 156 17 7 2 11.1 131 132 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 46 198.2 186 82 2.1 196 148.1 151 131.1 7.1 142 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198.3 172.1 132.1 65 72 64 75 12 191.1 151.1 146 163.1 12.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 47.1 75.1 17.1 47.2 75.2 62 151.2 146.1 64.1 116.2 160 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.1 46.1 22.1 7.2 71 144 19 31 182 200 44 102 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 67.1 84.1 62.1 172.2 67.2 116.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[95]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01783832 0.60260657 0.62455611
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.66231792 0.01301793 0.10265221
#> grade_iii, Cure model
#> 0.59745302
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 63 22.77 1 31 1 0
#> 39 15.59 1 37 0 1
#> 170 19.54 1 43 0 1
#> 23 16.92 1 61 0 0
#> 70 7.38 1 30 1 0
#> 194 22.40 1 38 0 1
#> 190 20.81 1 42 1 0
#> 134 17.81 1 47 1 0
#> 79 16.23 1 54 1 0
#> 114 13.68 1 NA 0 0
#> 155 13.08 1 26 0 0
#> 111 17.45 1 47 0 1
#> 125 15.65 1 67 1 0
#> 6 15.64 1 39 0 0
#> 91 5.33 1 61 0 1
#> 36 21.19 1 48 0 1
#> 70.1 7.38 1 30 1 0
#> 183 9.24 1 67 1 0
#> 140 12.68 1 59 1 0
#> 40 18.00 1 28 1 0
#> 81 14.06 1 34 0 0
#> 30 17.43 1 78 0 0
#> 113 22.86 1 34 0 0
#> 96 14.54 1 33 0 1
#> 32 20.90 1 37 1 0
#> 107 11.18 1 54 1 0
#> 78 23.88 1 43 0 0
#> 195 11.76 1 NA 1 0
#> 70.2 7.38 1 30 1 0
#> 70.3 7.38 1 30 1 0
#> 52 10.42 1 52 0 1
#> 157 15.10 1 47 0 0
#> 134.1 17.81 1 47 1 0
#> 10 10.53 1 34 0 0
#> 23.1 16.92 1 61 0 0
#> 192 16.44 1 31 1 0
#> 197 21.60 1 69 1 0
#> 16 8.71 1 71 0 1
#> 50 10.02 1 NA 1 0
#> 91.1 5.33 1 61 0 1
#> 5 16.43 1 51 0 1
#> 15 22.68 1 48 0 0
#> 180 14.82 1 37 0 0
#> 25 6.32 1 34 1 0
#> 181 16.46 1 45 0 1
#> 100 16.07 1 60 0 0
#> 105 19.75 1 60 0 0
#> 187 9.92 1 39 1 0
#> 129 23.41 1 53 1 0
#> 127 3.53 1 62 0 1
#> 171 16.57 1 41 0 1
#> 40.1 18.00 1 28 1 0
#> 159 10.55 1 50 0 1
#> 40.2 18.00 1 28 1 0
#> 91.2 5.33 1 61 0 1
#> 41 18.02 1 40 1 0
#> 166 19.98 1 48 0 0
#> 180.1 14.82 1 37 0 0
#> 89 11.44 1 NA 0 0
#> 139 21.49 1 63 1 0
#> 30.1 17.43 1 78 0 0
#> 177 12.53 1 75 0 0
#> 180.2 14.82 1 37 0 0
#> 78.1 23.88 1 43 0 0
#> 180.3 14.82 1 37 0 0
#> 124 9.73 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 39.1 15.59 1 37 0 1
#> 57 14.46 1 45 0 1
#> 78.2 23.88 1 43 0 0
#> 85 16.44 1 36 0 0
#> 90 20.94 1 50 0 1
#> 40.3 18.00 1 28 1 0
#> 52.1 10.42 1 52 0 1
#> 16.1 8.71 1 71 0 1
#> 159.1 10.55 1 50 0 1
#> 16.2 8.71 1 71 0 1
#> 159.2 10.55 1 50 0 1
#> 5.1 16.43 1 51 0 1
#> 37 12.52 1 57 1 0
#> 56 12.21 1 60 0 0
#> 124.1 9.73 1 NA 1 0
#> 171.1 16.57 1 41 0 1
#> 183.1 9.24 1 67 1 0
#> 92 22.92 1 47 0 1
#> 59 10.16 1 NA 1 0
#> 108 18.29 1 39 0 1
#> 61 10.12 1 36 0 1
#> 55 19.34 1 69 0 1
#> 92.1 22.92 1 47 0 1
#> 145 10.07 1 65 1 0
#> 194.1 22.40 1 38 0 1
#> 195.1 11.76 1 NA 1 0
#> 57.1 14.46 1 45 0 1
#> 167 15.55 1 56 1 0
#> 30.2 17.43 1 78 0 0
#> 194.2 22.40 1 38 0 1
#> 89.1 11.44 1 NA 0 0
#> 166.1 19.98 1 48 0 0
#> 89.2 11.44 1 NA 0 0
#> 78.3 23.88 1 43 0 0
#> 184 17.77 1 38 0 0
#> 18 15.21 1 49 1 0
#> 91.3 5.33 1 61 0 1
#> 78.4 23.88 1 43 0 0
#> 170.1 19.54 1 43 0 1
#> 29 15.45 1 68 1 0
#> 149 8.37 1 33 1 0
#> 181.1 16.46 1 45 0 1
#> 153 21.33 1 55 1 0
#> 128 20.35 1 35 0 1
#> 145.1 10.07 1 65 1 0
#> 74 24.00 0 43 0 1
#> 165 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 28 24.00 0 67 1 0
#> 28.1 24.00 0 67 1 0
#> 19 24.00 0 57 0 1
#> 165.1 24.00 0 47 0 0
#> 138 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 186 24.00 0 45 1 0
#> 162 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 104 24.00 0 50 1 0
#> 172 24.00 0 41 0 0
#> 148 24.00 0 61 1 0
#> 152 24.00 0 36 0 1
#> 38 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 151 24.00 0 42 0 0
#> 191 24.00 0 60 0 1
#> 19.1 24.00 0 57 0 1
#> 3 24.00 0 31 1 0
#> 27 24.00 0 63 1 0
#> 17 24.00 0 38 0 1
#> 174 24.00 0 49 1 0
#> 17.1 24.00 0 38 0 1
#> 11 24.00 0 42 0 1
#> 73 24.00 0 NA 0 1
#> 135 24.00 0 58 1 0
#> 84 24.00 0 39 0 1
#> 193 24.00 0 45 0 1
#> 196 24.00 0 19 0 0
#> 152.1 24.00 0 36 0 1
#> 73.1 24.00 0 NA 0 1
#> 80 24.00 0 41 0 0
#> 75 24.00 0 21 1 0
#> 71 24.00 0 51 0 0
#> 28.2 24.00 0 67 1 0
#> 173 24.00 0 19 0 1
#> 120.1 24.00 0 68 0 1
#> 31.1 24.00 0 36 0 1
#> 35 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#> 185 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 146 24.00 0 63 1 0
#> 102 24.00 0 49 0 0
#> 142 24.00 0 53 0 0
#> 82 24.00 0 34 0 0
#> 165.2 24.00 0 47 0 0
#> 65 24.00 0 57 1 0
#> 64 24.00 0 43 0 0
#> 103 24.00 0 56 1 0
#> 165.3 24.00 0 47 0 0
#> 84.1 24.00 0 39 0 1
#> 82.1 24.00 0 34 0 0
#> 71.1 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 132 24.00 0 55 0 0
#> 141 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 112 24.00 0 61 0 0
#> 137.1 24.00 0 45 1 0
#> 65.1 24.00 0 57 1 0
#> 160 24.00 0 31 1 0
#> 11.1 24.00 0 42 0 1
#> 82.2 24.00 0 34 0 0
#> 27.1 24.00 0 63 1 0
#> 162.1 24.00 0 51 0 0
#> 131 24.00 0 66 0 0
#> 122 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 7 24.00 0 37 1 0
#> 65.2 24.00 0 57 1 0
#> 9 24.00 0 31 1 0
#> 172.1 24.00 0 41 0 0
#> 38.1 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 137.2 24.00 0 45 1 0
#> 196.1 24.00 0 19 0 0
#> 132.1 24.00 0 55 0 0
#> 191.1 24.00 0 60 0 1
#> 54 24.00 0 53 1 0
#> 121 24.00 0 57 1 0
#> 53 24.00 0 32 0 1
#> 152.2 24.00 0 36 0 1
#> 64.1 24.00 0 43 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.662 NA NA NA
#> 2 age, Cure model 0.0130 NA NA NA
#> 3 grade_ii, Cure model 0.103 NA NA NA
#> 4 grade_iii, Cure model 0.597 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0178 NA NA NA
#> 2 grade_ii, Survival model 0.603 NA NA NA
#> 3 grade_iii, Survival model 0.625 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.66232 0.01302 0.10265 0.59745
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 254.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.66231792 0.01301793 0.10265221 0.59745302
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01783832 0.60260657 0.62455611
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.5059069 0.8505780 0.6893334 0.7858904 0.9737803 0.5404882 0.6410686
#> [8] 0.7475706 0.8334473 0.9040913 0.7647392 0.8421542 0.8463767 0.9872551
#> [15] 0.6132824 0.9737803 0.9567976 0.9077173 0.7236550 0.9004568 0.7703106
#> [22] 0.4867755 0.8894342 0.6321948 0.9217301 0.2639638 0.9737803 0.9737803
#> [29] 0.9381704 0.8705610 0.7475706 0.9349088 0.7858904 0.8152755 0.5800139
#> [36] 0.9626583 0.9872551 0.8245435 0.5235839 0.8744049 0.9845651 0.8058426
#> [43] 0.8378224 0.6816376 0.9537693 0.4199745 0.9974673 0.7960465 0.7236550
#> [50] 0.9251296 0.7236550 0.9872551 0.7171638 0.6659964 0.8744049 0.5920318
#> [57] 0.7703106 0.9112830 0.8744049 0.2639638 0.8744049 0.6578693 0.8505780
#> [64] 0.8931779 0.2639638 0.8152755 0.6229936 0.7236550 0.9381704 0.9626583
#> [71] 0.9251296 0.9626583 0.9251296 0.8245435 0.9148098 0.9182825 0.7960465
#> [78] 0.9567976 0.4480203 0.7105082 0.9445184 0.7036770 0.4480203 0.9476706
#> [85] 0.5404882 0.8931779 0.8587495 0.7703106 0.5404882 0.6659964 0.2639638
#> [92] 0.7590298 0.8666946 0.9872551 0.2639638 0.6893334 0.8627691 0.9710075
#> [99] 0.8058426 0.6030192 0.6496040 0.9476706 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 63 39 170 23 70 194 190 134 79 155 111 125 6
#> 22.77 15.59 19.54 16.92 7.38 22.40 20.81 17.81 16.23 13.08 17.45 15.65 15.64
#> 91 36 70.1 183 140 40 81 30 113 96 32 107 78
#> 5.33 21.19 7.38 9.24 12.68 18.00 14.06 17.43 22.86 14.54 20.90 11.18 23.88
#> 70.2 70.3 52 157 134.1 10 23.1 192 197 16 91.1 5 15
#> 7.38 7.38 10.42 15.10 17.81 10.53 16.92 16.44 21.60 8.71 5.33 16.43 22.68
#> 180 25 181 100 105 187 129 127 171 40.1 159 40.2 91.2
#> 14.82 6.32 16.46 16.07 19.75 9.92 23.41 3.53 16.57 18.00 10.55 18.00 5.33
#> 41 166 180.1 139 30.1 177 180.2 78.1 180.3 150 39.1 57 78.2
#> 18.02 19.98 14.82 21.49 17.43 12.53 14.82 23.88 14.82 20.33 15.59 14.46 23.88
#> 85 90 40.3 52.1 16.1 159.1 16.2 159.2 5.1 37 56 171.1 183.1
#> 16.44 20.94 18.00 10.42 8.71 10.55 8.71 10.55 16.43 12.52 12.21 16.57 9.24
#> 92 108 61 55 92.1 145 194.1 57.1 167 30.2 194.2 166.1 78.3
#> 22.92 18.29 10.12 19.34 22.92 10.07 22.40 14.46 15.55 17.43 22.40 19.98 23.88
#> 184 18 91.3 78.4 170.1 29 149 181.1 153 128 145.1 74 165
#> 17.77 15.21 5.33 23.88 19.54 15.45 8.37 16.46 21.33 20.35 10.07 24.00 24.00
#> 12 28 28.1 19 165.1 138 120 186 162 137 104 172 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 38 31 151 191 19.1 3 27 17 174 17.1 11 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 193 196 152.1 80 75 71 28.2 173 120.1 31.1 35 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 118 67 146 102 142 82 165.2 65 64 103 165.3 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.1 71.1 83 132 141 126 112 137.1 65.1 160 11.1 82.2 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.1 131 122 2 7 65.2 9 172.1 38.1 22 137.2 196.1 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.1 54 121 53 152.2 64.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[96]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01505796 0.87016142 0.31967555
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.404834679 0.008740368 -0.282943801
#> grade_iii, Cure model
#> 0.795565822
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 91 5.33 1 61 0 1
#> 154 12.63 1 20 1 0
#> 197 21.60 1 69 1 0
#> 170 19.54 1 43 0 1
#> 61 10.12 1 36 0 1
#> 51 18.23 1 83 0 1
#> 149 8.37 1 33 1 0
#> 195 11.76 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 194 22.40 1 38 0 1
#> 69 23.23 1 25 0 1
#> 77 7.27 1 67 0 1
#> 29 15.45 1 68 1 0
#> 61.1 10.12 1 36 0 1
#> 140 12.68 1 59 1 0
#> 76 19.22 1 54 0 1
#> 194.1 22.40 1 38 0 1
#> 68 20.62 1 44 0 0
#> 170.1 19.54 1 43 0 1
#> 139 21.49 1 63 1 0
#> 50 10.02 1 NA 1 0
#> 124 9.73 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 23 16.92 1 61 0 0
#> 100 16.07 1 60 0 0
#> 25 6.32 1 34 1 0
#> 52 10.42 1 52 0 1
#> 86 23.81 1 58 0 1
#> 57 14.46 1 45 0 1
#> 86.1 23.81 1 58 0 1
#> 197.1 21.60 1 69 1 0
#> 187 9.92 1 39 1 0
#> 43 12.10 1 61 0 1
#> 15 22.68 1 48 0 0
#> 136 21.83 1 43 0 1
#> 153 21.33 1 55 1 0
#> 113 22.86 1 34 0 0
#> 41 18.02 1 40 1 0
#> 29.1 15.45 1 68 1 0
#> 99 21.19 1 38 0 1
#> 125 15.65 1 67 1 0
#> 5 16.43 1 51 0 1
#> 15.1 22.68 1 48 0 0
#> 88 18.37 1 47 0 0
#> 140.1 12.68 1 59 1 0
#> 195.1 11.76 1 NA 1 0
#> 59 10.16 1 NA 1 0
#> 187.1 9.92 1 39 1 0
#> 133 14.65 1 57 0 0
#> 78 23.88 1 43 0 0
#> 36 21.19 1 48 0 1
#> 86.2 23.81 1 58 0 1
#> 14 12.89 1 21 0 0
#> 96 14.54 1 33 0 1
#> 14.1 12.89 1 21 0 0
#> 92 22.92 1 47 0 1
#> 39 15.59 1 37 0 1
#> 97 19.14 1 65 0 1
#> 101 9.97 1 10 0 1
#> 10 10.53 1 34 0 0
#> 24 23.89 1 38 0 0
#> 175 21.91 1 43 0 0
#> 58 19.34 1 39 0 0
#> 23.1 16.92 1 61 0 0
#> 63 22.77 1 31 1 0
#> 108 18.29 1 39 0 1
#> 85 16.44 1 36 0 0
#> 43.1 12.10 1 61 0 1
#> 15.2 22.68 1 48 0 0
#> 41.1 18.02 1 40 1 0
#> 180 14.82 1 37 0 0
#> 159 10.55 1 50 0 1
#> 164 23.60 1 76 0 1
#> 180.1 14.82 1 37 0 0
#> 79 16.23 1 54 1 0
#> 114 13.68 1 NA 0 0
#> 25.1 6.32 1 34 1 0
#> 97.1 19.14 1 65 0 1
#> 124.1 9.73 1 NA 1 0
#> 39.1 15.59 1 37 0 1
#> 24.1 23.89 1 38 0 0
#> 157 15.10 1 47 0 0
#> 177 12.53 1 75 0 0
#> 99.1 21.19 1 38 0 1
#> 39.2 15.59 1 37 0 1
#> 30 17.43 1 78 0 0
#> 86.3 23.81 1 58 0 1
#> 101.1 9.97 1 10 0 1
#> 153.1 21.33 1 55 1 0
#> 150 20.33 1 48 0 0
#> 124.2 9.73 1 NA 1 0
#> 79.1 16.23 1 54 1 0
#> 164.1 23.60 1 76 0 1
#> 154.1 12.63 1 20 1 0
#> 43.2 12.10 1 61 0 1
#> 70 7.38 1 30 1 0
#> 70.1 7.38 1 30 1 0
#> 39.3 15.59 1 37 0 1
#> 93 10.33 1 52 0 1
#> 168 23.72 1 70 0 0
#> 10.1 10.53 1 34 0 0
#> 171 16.57 1 41 0 1
#> 93.1 10.33 1 52 0 1
#> 97.2 19.14 1 65 0 1
#> 140.2 12.68 1 59 1 0
#> 68.1 20.62 1 44 0 0
#> 16 8.71 1 71 0 1
#> 93.2 10.33 1 52 0 1
#> 14.2 12.89 1 21 0 0
#> 183 9.24 1 67 1 0
#> 155 13.08 1 26 0 0
#> 181 16.46 1 45 0 1
#> 144 24.00 0 28 0 1
#> 174 24.00 0 49 1 0
#> 115 24.00 0 NA 1 0
#> 65 24.00 0 57 1 0
#> 196 24.00 0 19 0 0
#> 83 24.00 0 6 0 0
#> 156 24.00 0 50 1 0
#> 27 24.00 0 63 1 0
#> 71 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 31 24.00 0 36 0 1
#> 120 24.00 0 68 0 1
#> 83.1 24.00 0 6 0 0
#> 33 24.00 0 53 0 0
#> 20 24.00 0 46 1 0
#> 94 24.00 0 51 0 1
#> 44 24.00 0 56 0 0
#> 22 24.00 0 52 1 0
#> 109 24.00 0 48 0 0
#> 27.1 24.00 0 63 1 0
#> 71.1 24.00 0 51 0 0
#> 193 24.00 0 45 0 1
#> 176 24.00 0 43 0 1
#> 48 24.00 0 31 1 0
#> 20.1 24.00 0 46 1 0
#> 67 24.00 0 25 0 0
#> 35 24.00 0 51 0 0
#> 27.2 24.00 0 63 1 0
#> 67.1 24.00 0 25 0 0
#> 12 24.00 0 63 0 0
#> 98 24.00 0 34 1 0
#> 109.1 24.00 0 48 0 0
#> 38 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 20.2 24.00 0 46 1 0
#> 64 24.00 0 43 0 0
#> 82 24.00 0 34 0 0
#> 11 24.00 0 42 0 1
#> 121 24.00 0 57 1 0
#> 142 24.00 0 53 0 0
#> 120.1 24.00 0 68 0 1
#> 144.1 24.00 0 28 0 1
#> 7 24.00 0 37 1 0
#> 102 24.00 0 49 0 0
#> 151 24.00 0 42 0 0
#> 2.1 24.00 0 9 0 0
#> 146 24.00 0 63 1 0
#> 28 24.00 0 67 1 0
#> 84 24.00 0 39 0 1
#> 178 24.00 0 52 1 0
#> 103 24.00 0 56 1 0
#> 95 24.00 0 68 0 1
#> 174.1 24.00 0 49 1 0
#> 193.1 24.00 0 45 0 1
#> 34 24.00 0 36 0 0
#> 178.1 24.00 0 52 1 0
#> 34.1 24.00 0 36 0 0
#> 200 24.00 0 64 0 0
#> 31.1 24.00 0 36 0 1
#> 27.3 24.00 0 63 1 0
#> 82.1 24.00 0 34 0 0
#> 174.2 24.00 0 49 1 0
#> 116 24.00 0 58 0 1
#> 152 24.00 0 36 0 1
#> 144.2 24.00 0 28 0 1
#> 141 24.00 0 44 1 0
#> 64.1 24.00 0 43 0 0
#> 7.1 24.00 0 37 1 0
#> 174.3 24.00 0 49 1 0
#> 44.1 24.00 0 56 0 0
#> 54 24.00 0 53 1 0
#> 198 24.00 0 66 0 1
#> 72 24.00 0 40 0 1
#> 31.2 24.00 0 36 0 1
#> 54.1 24.00 0 53 1 0
#> 118 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 27.4 24.00 0 63 1 0
#> 47 24.00 0 38 0 1
#> 143.1 24.00 0 51 0 0
#> 98.1 24.00 0 34 1 0
#> 156.1 24.00 0 50 1 0
#> 174.4 24.00 0 49 1 0
#> 165 24.00 0 47 0 0
#> 38.1 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 118.1 24.00 0 44 1 0
#> 120.2 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.405 NA NA NA
#> 2 age, Cure model 0.00874 NA NA NA
#> 3 grade_ii, Cure model -0.283 NA NA NA
#> 4 grade_iii, Cure model 0.796 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0151 NA NA NA
#> 2 grade_ii, Survival model 0.870 NA NA NA
#> 3 grade_iii, Survival model 0.320 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.40483 0.00874 -0.28294 0.79557
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 252.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.404834679 0.008740368 -0.282943801 0.795565822
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01505796 0.87016142 0.31967555
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.987522965 0.653511954 0.103053747 0.196378157 0.811822868 0.278878246
#> [7] 0.912905405 0.338948836 0.074496973 0.031911339 0.950318301 0.478293711
#> [13] 0.811822868 0.617814423 0.222498260 0.074496973 0.163202350 0.196378157
#> [19] 0.117923046 0.179426987 0.318371488 0.413200902 0.962866013 0.761720862
#> [25] 0.006244375 0.558364600 0.006244375 0.103053747 0.862514735 0.688798636
#> [31] 0.055754585 0.095507265 0.125646275 0.043527501 0.288940626 0.478293711
#> [37] 0.140544097 0.424143278 0.381121140 0.055754585 0.259267718 0.617814423
#> [43] 0.862514735 0.534846466 0.003408678 0.140544097 0.006244375 0.582154734
#> [49] 0.546584985 0.582154734 0.037574528 0.435122356 0.231575797 0.837239448
#> [55] 0.737055261 0.000579354 0.088124056 0.213562743 0.318371488 0.049826509
#> [61] 0.269031017 0.370415631 0.688798636 0.055754585 0.288940626 0.511913821
#> [67] 0.724783505 0.021684476 0.511913821 0.391936415 0.962866013 0.231575797
#> [73] 0.435122356 0.000579354 0.500536408 0.676874367 0.140544097 0.435122356
#> [79] 0.308308514 0.006244375 0.837239448 0.125646275 0.187804152 0.391936415
#> [85] 0.021684476 0.653511954 0.688798636 0.925550341 0.925550341 0.435122356
#> [91] 0.774230880 0.017184792 0.737055261 0.349353240 0.774230880 0.231575797
#> [97] 0.617814423 0.163202350 0.900180727 0.774230880 0.582154734 0.887550208
#> [103] 0.570219471 0.359838061 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 91 154 197 170 61 51 149 106 194 69 77 29 61.1
#> 5.33 12.63 21.60 19.54 10.12 18.23 8.37 16.67 22.40 23.23 7.27 15.45 10.12
#> 140 76 194.1 68 170.1 139 128 23 100 25 52 86 57
#> 12.68 19.22 22.40 20.62 19.54 21.49 20.35 16.92 16.07 6.32 10.42 23.81 14.46
#> 86.1 197.1 187 43 15 136 153 113 41 29.1 99 125 5
#> 23.81 21.60 9.92 12.10 22.68 21.83 21.33 22.86 18.02 15.45 21.19 15.65 16.43
#> 15.1 88 140.1 187.1 133 78 36 86.2 14 96 14.1 92 39
#> 22.68 18.37 12.68 9.92 14.65 23.88 21.19 23.81 12.89 14.54 12.89 22.92 15.59
#> 97 101 10 24 175 58 23.1 63 108 85 43.1 15.2 41.1
#> 19.14 9.97 10.53 23.89 21.91 19.34 16.92 22.77 18.29 16.44 12.10 22.68 18.02
#> 180 159 164 180.1 79 25.1 97.1 39.1 24.1 157 177 99.1 39.2
#> 14.82 10.55 23.60 14.82 16.23 6.32 19.14 15.59 23.89 15.10 12.53 21.19 15.59
#> 30 86.3 101.1 153.1 150 79.1 164.1 154.1 43.2 70 70.1 39.3 93
#> 17.43 23.81 9.97 21.33 20.33 16.23 23.60 12.63 12.10 7.38 7.38 15.59 10.33
#> 168 10.1 171 93.1 97.2 140.2 68.1 16 93.2 14.2 183 155 181
#> 23.72 10.53 16.57 10.33 19.14 12.68 20.62 8.71 10.33 12.89 9.24 13.08 16.46
#> 144 174 65 196 83 156 27 71 62 31 120 83.1 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 94 44 22 109 27.1 71.1 193 176 48 20.1 67 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27.2 67.1 12 98 109.1 38 2 20.2 64 82 11 121 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 144.1 7 102 151 2.1 146 28 84 178 103 95 174.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.1 34 178.1 34.1 200 31.1 27.3 82.1 174.2 116 152 144.2 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.1 7.1 174.3 44.1 54 198 72 31.2 54.1 118 143 27.4 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143.1 98.1 156.1 174.4 165 38.1 87 118.1 120.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[97]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002911643 0.808513222 0.804478975
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.518362640 0.011675961 -0.006131798
#> grade_iii, Cure model
#> 0.589265350
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 129 23.41 1 53 1 0
#> 100 16.07 1 60 0 0
#> 194 22.40 1 38 0 1
#> 56 12.21 1 60 0 0
#> 68 20.62 1 44 0 0
#> 113 22.86 1 34 0 0
#> 78 23.88 1 43 0 0
#> 55 19.34 1 69 0 1
#> 32 20.90 1 37 1 0
#> 189 10.51 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 197 21.60 1 69 1 0
#> 41 18.02 1 40 1 0
#> 117 17.46 1 26 0 1
#> 107 11.18 1 54 1 0
#> 40 18.00 1 28 1 0
#> 154 12.63 1 20 1 0
#> 195 11.76 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 85 16.44 1 36 0 0
#> 41.1 18.02 1 40 1 0
#> 56.1 12.21 1 60 0 0
#> 13 14.34 1 54 0 1
#> 187 9.92 1 39 1 0
#> 127 3.53 1 62 0 1
#> 61 10.12 1 36 0 1
#> 61.1 10.12 1 36 0 1
#> 128 20.35 1 35 0 1
#> 42 12.43 1 49 0 1
#> 42.1 12.43 1 49 0 1
#> 123 13.00 1 44 1 0
#> 108 18.29 1 39 0 1
#> 96 14.54 1 33 0 1
#> 36 21.19 1 48 0 1
#> 91 5.33 1 61 0 1
#> 42.2 12.43 1 49 0 1
#> 157 15.10 1 47 0 0
#> 130 16.47 1 53 0 1
#> 68.1 20.62 1 44 0 0
#> 14 12.89 1 21 0 0
#> 29 15.45 1 68 1 0
#> 99 21.19 1 38 0 1
#> 29.1 15.45 1 68 1 0
#> 13.1 14.34 1 54 0 1
#> 113.1 22.86 1 34 0 0
#> 150 20.33 1 48 0 0
#> 158 20.14 1 74 1 0
#> 4 17.64 1 NA 0 1
#> 41.2 18.02 1 40 1 0
#> 24 23.89 1 38 0 0
#> 150.1 20.33 1 48 0 0
#> 68.2 20.62 1 44 0 0
#> 76 19.22 1 54 0 1
#> 39 15.59 1 37 0 1
#> 8 18.43 1 32 0 0
#> 45 17.42 1 54 0 1
#> 150.2 20.33 1 48 0 0
#> 79 16.23 1 54 1 0
#> 100.1 16.07 1 60 0 0
#> 63 22.77 1 31 1 0
#> 123.1 13.00 1 44 1 0
#> 89 11.44 1 NA 0 0
#> 166 19.98 1 48 0 0
#> 92 22.92 1 47 0 1
#> 39.1 15.59 1 37 0 1
#> 155 13.08 1 26 0 0
#> 181 16.46 1 45 0 1
#> 184 17.77 1 38 0 0
#> 140 12.68 1 59 1 0
#> 16 8.71 1 71 0 1
#> 16.1 8.71 1 71 0 1
#> 25 6.32 1 34 1 0
#> 108.1 18.29 1 39 0 1
#> 51 18.23 1 83 0 1
#> 170 19.54 1 43 0 1
#> 40.1 18.00 1 28 1 0
#> 157.1 15.10 1 47 0 0
#> 97 19.14 1 65 0 1
#> 149 8.37 1 33 1 0
#> 190 20.81 1 42 1 0
#> 8.1 18.43 1 32 0 0
#> 37 12.52 1 57 1 0
#> 49 12.19 1 48 1 0
#> 59 10.16 1 NA 1 0
#> 77 7.27 1 67 0 1
#> 107.1 11.18 1 54 1 0
#> 55.1 19.34 1 69 0 1
#> 36.1 21.19 1 48 0 1
#> 192 16.44 1 31 1 0
#> 180 14.82 1 37 0 0
#> 13.2 14.34 1 54 0 1
#> 166.1 19.98 1 48 0 0
#> 16.2 8.71 1 71 0 1
#> 168.1 23.72 1 70 0 0
#> 153 21.33 1 55 1 0
#> 183 9.24 1 67 1 0
#> 113.2 22.86 1 34 0 0
#> 124 9.73 1 NA 1 0
#> 56.2 12.21 1 60 0 0
#> 68.3 20.62 1 44 0 0
#> 51.1 18.23 1 83 0 1
#> 114 13.68 1 NA 0 0
#> 96.1 14.54 1 33 0 1
#> 106 16.67 1 49 1 0
#> 68.4 20.62 1 44 0 0
#> 45.1 17.42 1 54 0 1
#> 123.2 13.00 1 44 1 0
#> 68.5 20.62 1 44 0 0
#> 66 22.13 1 53 0 0
#> 169 22.41 1 46 0 0
#> 140.1 12.68 1 59 1 0
#> 49.1 12.19 1 48 1 0
#> 27 24.00 0 63 1 0
#> 7 24.00 0 37 1 0
#> 116 24.00 0 58 0 1
#> 121 24.00 0 57 1 0
#> 82 24.00 0 34 0 0
#> 95 24.00 0 68 0 1
#> 156 24.00 0 50 1 0
#> 200 24.00 0 64 0 0
#> 121.1 24.00 0 57 1 0
#> 64 24.00 0 43 0 0
#> 156.1 24.00 0 50 1 0
#> 21 24.00 0 47 0 0
#> 112 24.00 0 61 0 0
#> 103 24.00 0 56 1 0
#> 31 24.00 0 36 0 1
#> 122 24.00 0 66 0 0
#> 176 24.00 0 43 0 1
#> 118 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 74 24.00 0 43 0 1
#> 17 24.00 0 38 0 1
#> 173 24.00 0 19 0 1
#> 104.1 24.00 0 50 1 0
#> 122.1 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 83 24.00 0 6 0 0
#> 21.1 24.00 0 47 0 0
#> 1 24.00 0 23 1 0
#> 126 24.00 0 48 0 0
#> 35 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 118.1 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 103.1 24.00 0 56 1 0
#> 104.2 24.00 0 50 1 0
#> 46 24.00 0 71 0 0
#> 174 24.00 0 49 1 0
#> 165 24.00 0 47 0 0
#> 148 24.00 0 61 1 0
#> 144 24.00 0 28 0 1
#> 182 24.00 0 35 0 0
#> 62 24.00 0 71 0 0
#> 95.1 24.00 0 68 0 1
#> 103.2 24.00 0 56 1 0
#> 19 24.00 0 57 0 1
#> 2 24.00 0 9 0 0
#> 142 24.00 0 53 0 0
#> 27.1 24.00 0 63 1 0
#> 11 24.00 0 42 0 1
#> 152 24.00 0 36 0 1
#> 87.1 24.00 0 27 0 0
#> 156.2 24.00 0 50 1 0
#> 104.3 24.00 0 50 1 0
#> 172 24.00 0 41 0 0
#> 162 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 73 24.00 0 NA 0 1
#> 83.1 24.00 0 6 0 0
#> 132 24.00 0 55 0 0
#> 120 24.00 0 68 0 1
#> 152.1 24.00 0 36 0 1
#> 172.1 24.00 0 41 0 0
#> 82.1 24.00 0 34 0 0
#> 193 24.00 0 45 0 1
#> 9 24.00 0 31 1 0
#> 74.1 24.00 0 43 0 1
#> 74.2 24.00 0 43 0 1
#> 12 24.00 0 63 0 0
#> 161.1 24.00 0 45 0 0
#> 35.1 24.00 0 51 0 0
#> 109.1 24.00 0 48 0 0
#> 176.1 24.00 0 43 0 1
#> 73.1 24.00 0 NA 0 1
#> 116.1 24.00 0 58 0 1
#> 121.2 24.00 0 57 1 0
#> 98.1 24.00 0 34 1 0
#> 178 24.00 0 52 1 0
#> 2.1 24.00 0 9 0 0
#> 38 24.00 0 31 1 0
#> 2.2 24.00 0 9 0 0
#> 38.1 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 44 24.00 0 56 0 0
#> 172.2 24.00 0 41 0 0
#> 135 24.00 0 58 1 0
#> 48 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 54 24.00 0 53 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.518 NA NA NA
#> 2 age, Cure model 0.0117 NA NA NA
#> 3 grade_ii, Cure model -0.00613 NA NA NA
#> 4 grade_iii, Cure model 0.589 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00291 NA NA NA
#> 2 grade_ii, Survival model 0.809 NA NA NA
#> 3 grade_iii, Survival model 0.804 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.518363 0.011676 -0.006132 0.589265
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 257.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.518362640 0.011675961 -0.006131798 0.589265350
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002911643 0.808513222 0.804478975
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.16716322 0.76031224 0.31834946 0.90843715 0.43494811 0.21202753
#> [7] 0.07005602 0.57336925 0.41284886 0.28370072 0.35014107 0.65707252
#> [13] 0.70046609 0.93383232 0.67902803 0.88240953 0.10925300 0.74107797
#> [19] 0.65707252 0.90843715 0.82706146 0.95347208 0.99548947 0.94372794
#> [25] 0.94372794 0.49487314 0.89306166 0.89306166 0.84970005 0.62532158
#> [31] 0.81533091 0.37858741 0.99094439 0.89306166 0.79732534 0.72788745
#> [37] 0.43494811 0.86613596 0.78530665 0.37858741 0.78530665 0.82706146
#> [43] 0.21202753 0.50508475 0.53483975 0.65707252 0.02861801 0.50508475
#> [49] 0.43494811 0.59114843 0.77295993 0.60842356 0.70752911 0.50508475
#> [55] 0.75394156 0.76031224 0.26614399 0.84970005 0.54461819 0.19162736
#> [61] 0.77295993 0.84401397 0.73452856 0.69330111 0.87164740 0.96312403
#> [67] 0.96312403 0.98636423 0.62532158 0.64155955 0.56389668 0.67902803
#> [73] 0.79732534 0.59989177 0.97710310 0.42411954 0.60842356 0.88776195
#> [79] 0.92376313 0.98175242 0.93383232 0.57336925 0.37858741 0.74107797
#> [85] 0.80931752 0.82706146 0.54461819 0.96312403 0.10925300 0.36481684
#> [91] 0.95831905 0.21202753 0.90843715 0.43494811 0.64155955 0.81533091
#> [97] 0.72114743 0.43494811 0.70752911 0.84970005 0.43494811 0.33430824
#> [103] 0.30109636 0.87164740 0.92376313 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 129 100 194 56 68 113 78 55 32 15 197 41 117
#> 23.41 16.07 22.40 12.21 20.62 22.86 23.88 19.34 20.90 22.68 21.60 18.02 17.46
#> 107 40 154 168 85 41.1 56.1 13 187 127 61 61.1 128
#> 11.18 18.00 12.63 23.72 16.44 18.02 12.21 14.34 9.92 3.53 10.12 10.12 20.35
#> 42 42.1 123 108 96 36 91 42.2 157 130 68.1 14 29
#> 12.43 12.43 13.00 18.29 14.54 21.19 5.33 12.43 15.10 16.47 20.62 12.89 15.45
#> 99 29.1 13.1 113.1 150 158 41.2 24 150.1 68.2 76 39 8
#> 21.19 15.45 14.34 22.86 20.33 20.14 18.02 23.89 20.33 20.62 19.22 15.59 18.43
#> 45 150.2 79 100.1 63 123.1 166 92 39.1 155 181 184 140
#> 17.42 20.33 16.23 16.07 22.77 13.00 19.98 22.92 15.59 13.08 16.46 17.77 12.68
#> 16 16.1 25 108.1 51 170 40.1 157.1 97 149 190 8.1 37
#> 8.71 8.71 6.32 18.29 18.23 19.54 18.00 15.10 19.14 8.37 20.81 18.43 12.52
#> 49 77 107.1 55.1 36.1 192 180 13.2 166.1 16.2 168.1 153 183
#> 12.19 7.27 11.18 19.34 21.19 16.44 14.82 14.34 19.98 8.71 23.72 21.33 9.24
#> 113.2 56.2 68.3 51.1 96.1 106 68.4 45.1 123.2 68.5 66 169 140.1
#> 22.86 12.21 20.62 18.23 14.54 16.67 20.62 17.42 13.00 20.62 22.13 22.41 12.68
#> 49.1 27 7 116 121 82 95 156 200 121.1 64 156.1 21
#> 12.19 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 103 31 122 176 118 104 74 17 173 104.1 122.1 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 21.1 1 126 35 98 118.1 109 103.1 104.2 46 174 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 144 182 62 95.1 103.2 19 2 142 27.1 11 152 87.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.2 104.3 172 162 161 83.1 132 120 152.1 172.1 82.1 193 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.1 74.2 12 161.1 35.1 109.1 176.1 116.1 121.2 98.1 178 2.1 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.2 38.1 53 44 172.2 135 48 146 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[98]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00696129 0.96362066 0.98686197
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.806851624 0.005256473 0.753866188
#> grade_iii, Cure model
#> 1.378527376
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 16 8.71 1 71 0 1
#> 167 15.55 1 56 1 0
#> 42 12.43 1 49 0 1
#> 60 13.15 1 38 1 0
#> 181 16.46 1 45 0 1
#> 18 15.21 1 49 1 0
#> 167.1 15.55 1 56 1 0
#> 97 19.14 1 65 0 1
#> 40 18.00 1 28 1 0
#> 136 21.83 1 43 0 1
#> 159 10.55 1 50 0 1
#> 197 21.60 1 69 1 0
#> 26 15.77 1 49 0 1
#> 187 9.92 1 39 1 0
#> 42.1 12.43 1 49 0 1
#> 43 12.10 1 61 0 1
#> 26.1 15.77 1 49 0 1
#> 58 19.34 1 39 0 0
#> 52 10.42 1 52 0 1
#> 125 15.65 1 67 1 0
#> 29 15.45 1 68 1 0
#> 43.1 12.10 1 61 0 1
#> 113 22.86 1 34 0 0
#> 168 23.72 1 70 0 0
#> 76 19.22 1 54 0 1
#> 157 15.10 1 47 0 0
#> 140 12.68 1 59 1 0
#> 107 11.18 1 54 1 0
#> 195 11.76 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 110 17.56 1 65 0 1
#> 167.2 15.55 1 56 1 0
#> 188 16.16 1 46 0 1
#> 127 3.53 1 62 0 1
#> 187.1 9.92 1 39 1 0
#> 45 17.42 1 54 0 1
#> 136.1 21.83 1 43 0 1
#> 129 23.41 1 53 1 0
#> 57 14.46 1 45 0 1
#> 26.2 15.77 1 49 0 1
#> 32 20.90 1 37 1 0
#> 188.1 16.16 1 46 0 1
#> 4 17.64 1 NA 0 1
#> 97.1 19.14 1 65 0 1
#> 25 6.32 1 34 1 0
#> 134 17.81 1 47 1 0
#> 63 22.77 1 31 1 0
#> 136.2 21.83 1 43 0 1
#> 113.1 22.86 1 34 0 0
#> 4.1 17.64 1 NA 0 1
#> 41 18.02 1 40 1 0
#> 79 16.23 1 54 1 0
#> 169 22.41 1 46 0 0
#> 139 21.49 1 63 1 0
#> 59 10.16 1 NA 1 0
#> 76.1 19.22 1 54 0 1
#> 107.1 11.18 1 54 1 0
#> 45.1 17.42 1 54 0 1
#> 61 10.12 1 36 0 1
#> 113.2 22.86 1 34 0 0
#> 26.3 15.77 1 49 0 1
#> 168.1 23.72 1 70 0 0
#> 29.1 15.45 1 68 1 0
#> 24 23.89 1 38 0 0
#> 101 9.97 1 10 0 1
#> 15 22.68 1 48 0 0
#> 101.1 9.97 1 10 0 1
#> 140.1 12.68 1 59 1 0
#> 170 19.54 1 43 0 1
#> 58.1 19.34 1 39 0 0
#> 130 16.47 1 53 0 1
#> 55 19.34 1 69 0 1
#> 100 16.07 1 60 0 0
#> 26.4 15.77 1 49 0 1
#> 5 16.43 1 51 0 1
#> 77 7.27 1 67 0 1
#> 36 21.19 1 48 0 1
#> 180 14.82 1 37 0 0
#> 81 14.06 1 34 0 0
#> 43.2 12.10 1 61 0 1
#> 51 18.23 1 83 0 1
#> 127.1 3.53 1 62 0 1
#> 58.2 19.34 1 39 0 0
#> 136.3 21.83 1 43 0 1
#> 154 12.63 1 20 1 0
#> 70 7.38 1 30 1 0
#> 159.1 10.55 1 50 0 1
#> 77.1 7.27 1 67 0 1
#> 32.1 20.90 1 37 1 0
#> 97.2 19.14 1 65 0 1
#> 190 20.81 1 42 1 0
#> 192 16.44 1 31 1 0
#> 60.1 13.15 1 38 1 0
#> 157.1 15.10 1 47 0 0
#> 96 14.54 1 33 0 1
#> 164 23.60 1 76 0 1
#> 171 16.57 1 41 0 1
#> 13 14.34 1 54 0 1
#> 66 22.13 1 53 0 0
#> 76.2 19.22 1 54 0 1
#> 6 15.64 1 39 0 0
#> 91 5.33 1 61 0 1
#> 37 12.52 1 57 1 0
#> 136.4 21.83 1 43 0 1
#> 117 17.46 1 26 0 1
#> 100.1 16.07 1 60 0 0
#> 190.1 20.81 1 42 1 0
#> 51.1 18.23 1 83 0 1
#> 179 18.63 1 42 0 0
#> 90 20.94 1 50 0 1
#> 41.1 18.02 1 40 1 0
#> 81.1 14.06 1 34 0 0
#> 146 24.00 0 63 1 0
#> 148 24.00 0 61 1 0
#> 156 24.00 0 50 1 0
#> 31 24.00 0 36 0 1
#> 118 24.00 0 44 1 0
#> 94 24.00 0 51 0 1
#> 198 24.00 0 66 0 1
#> 2 24.00 0 9 0 0
#> 120 24.00 0 68 0 1
#> 141 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 7 24.00 0 37 1 0
#> 38 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 84 24.00 0 39 0 1
#> 1 24.00 0 23 1 0
#> 62 24.00 0 71 0 0
#> 163 24.00 0 66 0 0
#> 67 24.00 0 25 0 0
#> 162 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 72 24.00 0 40 0 1
#> 53 24.00 0 32 0 1
#> 109.1 24.00 0 48 0 0
#> 132 24.00 0 55 0 0
#> 109.2 24.00 0 48 0 0
#> 165 24.00 0 47 0 0
#> 126 24.00 0 48 0 0
#> 163.1 24.00 0 66 0 0
#> 143 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 12 24.00 0 63 0 0
#> 2.1 24.00 0 9 0 0
#> 83 24.00 0 6 0 0
#> 141.1 24.00 0 44 1 0
#> 165.1 24.00 0 47 0 0
#> 121 24.00 0 57 1 0
#> 84.1 24.00 0 39 0 1
#> 144 24.00 0 28 0 1
#> 98 24.00 0 34 1 0
#> 146.1 24.00 0 63 1 0
#> 132.1 24.00 0 55 0 0
#> 44 24.00 0 56 0 0
#> 143.1 24.00 0 51 0 0
#> 120.1 24.00 0 68 0 1
#> 176 24.00 0 43 0 1
#> 21 24.00 0 47 0 0
#> 119 24.00 0 17 0 0
#> 103 24.00 0 56 1 0
#> 12.1 24.00 0 63 0 0
#> 103.1 24.00 0 56 1 0
#> 87.1 24.00 0 27 0 0
#> 71 24.00 0 51 0 0
#> 165.2 24.00 0 47 0 0
#> 72.1 24.00 0 40 0 1
#> 142 24.00 0 53 0 0
#> 74 24.00 0 43 0 1
#> 121.1 24.00 0 57 1 0
#> 28 24.00 0 67 1 0
#> 115 24.00 0 NA 1 0
#> 191 24.00 0 60 0 1
#> 28.1 24.00 0 67 1 0
#> 62.1 24.00 0 71 0 0
#> 160 24.00 0 31 1 0
#> 1.1 24.00 0 23 1 0
#> 46 24.00 0 71 0 0
#> 19.1 24.00 0 57 0 1
#> 28.2 24.00 0 67 1 0
#> 64 24.00 0 43 0 0
#> 121.2 24.00 0 57 1 0
#> 116 24.00 0 58 0 1
#> 122 24.00 0 66 0 0
#> 87.2 24.00 0 27 0 0
#> 126.1 24.00 0 48 0 0
#> 174 24.00 0 49 1 0
#> 17 24.00 0 38 0 1
#> 156.1 24.00 0 50 1 0
#> 102 24.00 0 49 0 0
#> 176.1 24.00 0 43 0 1
#> 47 24.00 0 38 0 1
#> 28.3 24.00 0 67 1 0
#> 141.2 24.00 0 44 1 0
#> 47.1 24.00 0 38 0 1
#> 65 24.00 0 57 1 0
#> 72.2 24.00 0 40 0 1
#> 141.3 24.00 0 44 1 0
#> 87.3 24.00 0 27 0 0
#> 31.1 24.00 0 36 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.807 NA NA NA
#> 2 age, Cure model 0.00526 NA NA NA
#> 3 grade_ii, Cure model 0.754 NA NA NA
#> 4 grade_iii, Cure model 1.38 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00696 NA NA NA
#> 2 grade_ii, Survival model 0.964 NA NA NA
#> 3 grade_iii, Survival model 0.987 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.806852 0.005256 0.753866 1.378527
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 251.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.806851624 0.005256473 0.753866188 1.378527376
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00696129 0.96362066 0.98686197
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.954405766 0.728568626 0.863110017 0.823980502 0.618500396 0.762957591
#> [7] 0.728568626 0.478859921 0.551814064 0.243579329 0.906707284 0.305902950
#> [13] 0.679297318 0.942763539 0.863110017 0.875770455 0.679297318 0.410129659
#> [19] 0.918877916 0.714342165 0.749259614 0.875770455 0.114568471 0.026419449
#> [25] 0.450137483 0.769784436 0.837162801 0.894388801 0.569210924 0.728568626
#> [31] 0.649507387 0.988788806 0.942763539 0.586150684 0.243579329 0.095165329
#> [37] 0.797125739 0.679297318 0.356550823 0.649507387 0.478859921 0.977425157
#> [43] 0.560572535 0.168666760 0.243579329 0.114568471 0.534113710 0.641879461
#> [49] 0.205145690 0.319161811 0.450137483 0.894388801 0.586150684 0.924948504
#> [55] 0.114568471 0.679297318 0.026419449 0.749259614 0.007179884 0.930976048
#> [61] 0.186652630 0.930976048 0.837162801 0.399754458 0.410129659 0.610508826
#> [67] 0.410129659 0.664345339 0.679297318 0.634178335 0.965998971 0.332051035
#> [73] 0.783444897 0.810581291 0.875770455 0.515816752 0.988788806 0.410129659
#> [79] 0.243579329 0.850193618 0.960222089 0.906707284 0.965998971 0.356550823
#> [85] 0.478859921 0.378741225 0.626393924 0.823980502 0.769784436 0.790318832
#> [91] 0.071954342 0.602426801 0.803877224 0.224107999 0.450137483 0.721447058
#> [97] 0.983119370 0.856670383 0.243579329 0.577757695 0.664345339 0.378741225
#> [103] 0.515816752 0.506415644 0.344495591 0.534113710 0.810581291 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000
#>
#> $Time
#> 16 167 42 60 181 18 167.1 97 40 136 159 197 26
#> 8.71 15.55 12.43 13.15 16.46 15.21 15.55 19.14 18.00 21.83 10.55 21.60 15.77
#> 187 42.1 43 26.1 58 52 125 29 43.1 113 168 76 157
#> 9.92 12.43 12.10 15.77 19.34 10.42 15.65 15.45 12.10 22.86 23.72 19.22 15.10
#> 140 107 110 167.2 188 127 187.1 45 136.1 129 57 26.2 32
#> 12.68 11.18 17.56 15.55 16.16 3.53 9.92 17.42 21.83 23.41 14.46 15.77 20.90
#> 188.1 97.1 25 134 63 136.2 113.1 41 79 169 139 76.1 107.1
#> 16.16 19.14 6.32 17.81 22.77 21.83 22.86 18.02 16.23 22.41 21.49 19.22 11.18
#> 45.1 61 113.2 26.3 168.1 29.1 24 101 15 101.1 140.1 170 58.1
#> 17.42 10.12 22.86 15.77 23.72 15.45 23.89 9.97 22.68 9.97 12.68 19.54 19.34
#> 130 55 100 26.4 5 77 36 180 81 43.2 51 127.1 58.2
#> 16.47 19.34 16.07 15.77 16.43 7.27 21.19 14.82 14.06 12.10 18.23 3.53 19.34
#> 136.3 154 70 159.1 77.1 32.1 97.2 190 192 60.1 157.1 96 164
#> 21.83 12.63 7.38 10.55 7.27 20.90 19.14 20.81 16.44 13.15 15.10 14.54 23.60
#> 171 13 66 76.2 6 91 37 136.4 117 100.1 190.1 51.1 179
#> 16.57 14.34 22.13 19.22 15.64 5.33 12.52 21.83 17.46 16.07 20.81 18.23 18.63
#> 90 41.1 81.1 146 148 156 31 118 94 198 2 120 141
#> 20.94 18.02 14.06 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 7 38 109 84 1 62 163 67 162 19 72 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109.1 132 109.2 165 126 163.1 143 87 12 2.1 83 141.1 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 84.1 144 98 146.1 132.1 44 143.1 120.1 176 21 119 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12.1 103.1 87.1 71 165.2 72.1 142 74 121.1 28 191 28.1 62.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 1.1 46 19.1 28.2 64 121.2 116 122 87.2 126.1 174 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.1 102 176.1 47 28.3 141.2 47.1 65 72.2 141.3 87.3 31.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[99]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01066794 0.87447224 0.46456086
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.1105604482 -0.0004771914 -0.2221663228
#> grade_iii, Cure model
#> 0.4605658671
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 60 13.15 1 38 1 0
#> 158 20.14 1 74 1 0
#> 111 17.45 1 47 0 1
#> 175 21.91 1 43 0 0
#> 113 22.86 1 34 0 0
#> 63 22.77 1 31 1 0
#> 150 20.33 1 48 0 0
#> 197 21.60 1 69 1 0
#> 128 20.35 1 35 0 1
#> 18 15.21 1 49 1 0
#> 150.1 20.33 1 48 0 0
#> 108 18.29 1 39 0 1
#> 59 10.16 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 113.1 22.86 1 34 0 0
#> 164 23.60 1 76 0 1
#> 139 21.49 1 63 1 0
#> 93 10.33 1 52 0 1
#> 91 5.33 1 61 0 1
#> 145 10.07 1 65 1 0
#> 56 12.21 1 60 0 0
#> 127 3.53 1 62 0 1
#> 159 10.55 1 50 0 1
#> 169 22.41 1 46 0 0
#> 77 7.27 1 67 0 1
#> 175.1 21.91 1 43 0 0
#> 166 19.98 1 48 0 0
#> 26 15.77 1 49 0 1
#> 166.1 19.98 1 48 0 0
#> 60.1 13.15 1 38 1 0
#> 92 22.92 1 47 0 1
#> 114 13.68 1 NA 0 0
#> 89 11.44 1 NA 0 0
#> 59.1 10.16 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 189 10.51 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 101 9.97 1 10 0 1
#> 107 11.18 1 54 1 0
#> 139.1 21.49 1 63 1 0
#> 195 11.76 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 50 10.02 1 NA 1 0
#> 92.1 22.92 1 47 0 1
#> 168.1 23.72 1 70 0 0
#> 86 23.81 1 58 0 1
#> 194 22.40 1 38 0 1
#> 157 15.10 1 47 0 0
#> 79 16.23 1 54 1 0
#> 43 12.10 1 61 0 1
#> 40 18.00 1 28 1 0
#> 36 21.19 1 48 0 1
#> 175.2 21.91 1 43 0 0
#> 134 17.81 1 47 1 0
#> 49 12.19 1 48 1 0
#> 133 14.65 1 57 0 0
#> 70 7.38 1 30 1 0
#> 113.2 22.86 1 34 0 0
#> 154 12.63 1 20 1 0
#> 58 19.34 1 39 0 0
#> 56.1 12.21 1 60 0 0
#> 153 21.33 1 55 1 0
#> 157.1 15.10 1 47 0 0
#> 66 22.13 1 53 0 0
#> 101.1 9.97 1 10 0 1
#> 51 18.23 1 83 0 1
#> 18.1 15.21 1 49 1 0
#> 155 13.08 1 26 0 0
#> 90 20.94 1 50 0 1
#> 55.1 19.34 1 69 0 1
#> 60.2 13.15 1 38 1 0
#> 81 14.06 1 34 0 0
#> 168.2 23.72 1 70 0 0
#> 42 12.43 1 49 0 1
#> 97 19.14 1 65 0 1
#> 69 23.23 1 25 0 1
#> 36.1 21.19 1 48 0 1
#> 134.1 17.81 1 47 1 0
#> 149.1 8.37 1 33 1 0
#> 15 22.68 1 48 0 0
#> 179 18.63 1 42 0 0
#> 41 18.02 1 40 1 0
#> 55.2 19.34 1 69 0 1
#> 97.1 19.14 1 65 0 1
#> 24 23.89 1 38 0 0
#> 5 16.43 1 51 0 1
#> 23 16.92 1 61 0 0
#> 159.1 10.55 1 50 0 1
#> 127.1 3.53 1 62 0 1
#> 100 16.07 1 60 0 0
#> 111.1 17.45 1 47 0 1
#> 189.1 10.51 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 25 6.32 1 34 1 0
#> 199.1 19.81 1 NA 0 1
#> 113.3 22.86 1 34 0 0
#> 164.1 23.60 1 76 0 1
#> 13.1 14.34 1 54 0 1
#> 8 18.43 1 32 0 0
#> 23.1 16.92 1 61 0 0
#> 107.1 11.18 1 54 1 0
#> 153.1 21.33 1 55 1 0
#> 58.1 19.34 1 39 0 0
#> 128.1 20.35 1 35 0 1
#> 177 12.53 1 75 0 0
#> 153.2 21.33 1 55 1 0
#> 154.1 12.63 1 20 1 0
#> 51.1 18.23 1 83 0 1
#> 150.2 20.33 1 48 0 0
#> 85 16.44 1 36 0 0
#> 175.3 21.91 1 43 0 0
#> 93.1 10.33 1 52 0 1
#> 122 24.00 0 66 0 0
#> 3 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 34 24.00 0 36 0 0
#> 34.1 24.00 0 36 0 0
#> 178 24.00 0 52 1 0
#> 102 24.00 0 49 0 0
#> 1 24.00 0 23 1 0
#> 71 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 138 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 200 24.00 0 64 0 0
#> 151 24.00 0 42 0 0
#> 9 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 22 24.00 0 52 1 0
#> 104 24.00 0 50 1 0
#> 137 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 146.1 24.00 0 63 1 0
#> 19.1 24.00 0 57 0 1
#> 22.1 24.00 0 52 1 0
#> 28 24.00 0 67 1 0
#> 121 24.00 0 57 1 0
#> 126 24.00 0 48 0 0
#> 75 24.00 0 21 1 0
#> 152 24.00 0 36 0 1
#> 1.1 24.00 0 23 1 0
#> 132 24.00 0 55 0 0
#> 141 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 71.1 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 131 24.00 0 66 0 0
#> 47 24.00 0 38 0 1
#> 17.1 24.00 0 38 0 1
#> 19.2 24.00 0 57 0 1
#> 87 24.00 0 27 0 0
#> 80 24.00 0 41 0 0
#> 94 24.00 0 51 0 1
#> 62 24.00 0 71 0 0
#> 131.1 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 178.1 24.00 0 52 1 0
#> 191 24.00 0 60 0 1
#> 182 24.00 0 35 0 0
#> 132.1 24.00 0 55 0 0
#> 185 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 120 24.00 0 68 0 1
#> 161 24.00 0 45 0 0
#> 38 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 109 24.00 0 48 0 0
#> 71.2 24.00 0 51 0 0
#> 191.1 24.00 0 60 0 1
#> 65 24.00 0 57 1 0
#> 28.1 24.00 0 67 1 0
#> 35 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 19.3 24.00 0 57 0 1
#> 80.1 24.00 0 41 0 0
#> 126.1 24.00 0 48 0 0
#> 120.1 24.00 0 68 0 1
#> 46 24.00 0 71 0 0
#> 53 24.00 0 32 0 1
#> 174 24.00 0 49 1 0
#> 34.2 24.00 0 36 0 0
#> 161.1 24.00 0 45 0 0
#> 94.1 24.00 0 51 0 1
#> 144 24.00 0 28 0 1
#> 95 24.00 0 68 0 1
#> 131.2 24.00 0 66 0 0
#> 178.2 24.00 0 52 1 0
#> 163.1 24.00 0 66 0 0
#> 98 24.00 0 34 1 0
#> 103.1 24.00 0 56 1 0
#> 17.2 24.00 0 38 0 1
#> 148 24.00 0 61 1 0
#> 11 24.00 0 42 0 1
#> 151.1 24.00 0 42 0 0
#> 112 24.00 0 61 0 0
#> 144.1 24.00 0 28 0 1
#> 156.1 24.00 0 50 1 0
#> 75.1 24.00 0 21 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.111 NA NA NA
#> 2 age, Cure model -0.000477 NA NA NA
#> 3 grade_ii, Cure model -0.222 NA NA NA
#> 4 grade_iii, Cure model 0.461 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0107 NA NA NA
#> 2 grade_ii, Survival model 0.874 NA NA NA
#> 3 grade_iii, Survival model 0.465 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.1105604 -0.0004772 -0.2221663 0.4605659
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 257.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.1105604482 -0.0004771914 -0.2221663228 0.4605658671
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01066794 0.87447224 0.46456086
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.700312946 0.322236333 0.519375143 0.149075266 0.069423774 0.102407485
#> [7] 0.293233532 0.187650987 0.274328246 0.614747310 0.293233532 0.444750493
#> [13] 0.010149136 0.069423774 0.028102985 0.198056267 0.867347300 0.969790682
#> [19] 0.888180668 0.783740655 0.979870474 0.846557014 0.120481832 0.949595644
#> [25] 0.149075266 0.332182115 0.603990144 0.332182115 0.700312946 0.053186395
#> [31] 0.919216282 0.898634685 0.825800659 0.198056267 0.352250475 0.053186395
#> [37] 0.010149136 0.005265373 0.129946136 0.635766138 0.582588700 0.815263778
#> [43] 0.488062274 0.245670294 0.149075266 0.498707148 0.804749982 0.657062632
#> [49] 0.939486509 0.069423774 0.742290111 0.352250475 0.783740655 0.217867586
#> [55] 0.635766138 0.139368921 0.898634685 0.455547117 0.614747310 0.731653211
#> [61] 0.264642293 0.352250475 0.700312946 0.689409935 0.010149136 0.773297885
#> [67] 0.402205919 0.044458740 0.245670294 0.498707148 0.919216282 0.111297544
#> [73] 0.423208514 0.477233552 0.352250475 0.402205919 0.001175011 0.571865418
#> [79] 0.540073027 0.846557014 0.979870474 0.593243798 0.519375143 0.667879110
#> [85] 0.959728658 0.069423774 0.028102985 0.667879110 0.433940839 0.540073027
#> [91] 0.825800659 0.217867586 0.352250475 0.274328246 0.762863079 0.217867586
#> [97] 0.742290111 0.455547117 0.293233532 0.561157487 0.149075266 0.867347300
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 60 158 111 175 113 63 150 197 128 18 150.1 108 168
#> 13.15 20.14 17.45 21.91 22.86 22.77 20.33 21.60 20.35 15.21 20.33 18.29 23.72
#> 113.1 164 139 93 91 145 56 127 159 169 77 175.1 166
#> 22.86 23.60 21.49 10.33 5.33 10.07 12.21 3.53 10.55 22.41 7.27 21.91 19.98
#> 26 166.1 60.1 92 149 101 107 139.1 55 92.1 168.1 86 194
#> 15.77 19.98 13.15 22.92 8.37 9.97 11.18 21.49 19.34 22.92 23.72 23.81 22.40
#> 157 79 43 40 36 175.2 134 49 133 70 113.2 154 58
#> 15.10 16.23 12.10 18.00 21.19 21.91 17.81 12.19 14.65 7.38 22.86 12.63 19.34
#> 56.1 153 157.1 66 101.1 51 18.1 155 90 55.1 60.2 81 168.2
#> 12.21 21.33 15.10 22.13 9.97 18.23 15.21 13.08 20.94 19.34 13.15 14.06 23.72
#> 42 97 69 36.1 134.1 149.1 15 179 41 55.2 97.1 24 5
#> 12.43 19.14 23.23 21.19 17.81 8.37 22.68 18.63 18.02 19.34 19.14 23.89 16.43
#> 23 159.1 127.1 100 111.1 13 25 113.3 164.1 13.1 8 23.1 107.1
#> 16.92 10.55 3.53 16.07 17.45 14.34 6.32 22.86 23.60 14.34 18.43 16.92 11.18
#> 153.1 58.1 128.1 177 153.2 154.1 51.1 150.2 85 175.3 93.1 122 3
#> 21.33 19.34 20.35 12.53 21.33 12.63 18.23 20.33 16.44 21.91 10.33 24.00 24.00
#> 64 34 34.1 178 102 1 71 146 138 17 200 151 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 22 104 137 163 146.1 19.1 22.1 28 121 126 75 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.1 132 141 198 71.1 131 47 17.1 19.2 87 80 94 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 21 178.1 191 182 132.1 185 118 48 156 120 161 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 109 71.2 191.1 65 28.1 35 103 19.3 80.1 126.1 120.1 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 174 34.2 161.1 94.1 144 95 131.2 178.2 163.1 98 103.1 17.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 11 151.1 112 144.1 156.1 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[100]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008794123 0.256437568 -0.287145636
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.567025003 0.008579176 0.006108458
#> grade_iii, Cure model
#> 1.071733929
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55d6f034ab78>
#>
#> $data
#> time status age grade_ii grade_iii
#> 6 15.64 1 39 0 0
#> 51 18.23 1 83 0 1
#> 171 16.57 1 41 0 1
#> 8 18.43 1 32 0 0
#> 170 19.54 1 43 0 1
#> 89 11.44 1 NA 0 0
#> 29 15.45 1 68 1 0
#> 6.1 15.64 1 39 0 0
#> 36 21.19 1 48 0 1
#> 37 12.52 1 57 1 0
#> 184 17.77 1 38 0 0
#> 157 15.10 1 47 0 0
#> 111 17.45 1 47 0 1
#> 153 21.33 1 55 1 0
#> 114 13.68 1 NA 0 0
#> 96 14.54 1 33 0 1
#> 130 16.47 1 53 0 1
#> 29.1 15.45 1 68 1 0
#> 164 23.60 1 76 0 1
#> 183 9.24 1 67 1 0
#> 29.2 15.45 1 68 1 0
#> 5 16.43 1 51 0 1
#> 77 7.27 1 67 0 1
#> 168 23.72 1 70 0 0
#> 170.1 19.54 1 43 0 1
#> 192 16.44 1 31 1 0
#> 23 16.92 1 61 0 0
#> 108 18.29 1 39 0 1
#> 60 13.15 1 38 1 0
#> 140 12.68 1 59 1 0
#> 177 12.53 1 75 0 0
#> 92 22.92 1 47 0 1
#> 167 15.55 1 56 1 0
#> 39 15.59 1 37 0 1
#> 175 21.91 1 43 0 0
#> 188 16.16 1 46 0 1
#> 97 19.14 1 65 0 1
#> 130.1 16.47 1 53 0 1
#> 14 12.89 1 21 0 0
#> 194 22.40 1 38 0 1
#> 57 14.46 1 45 0 1
#> 81 14.06 1 34 0 0
#> 199 19.81 1 NA 0 1
#> 181 16.46 1 45 0 1
#> 105 19.75 1 60 0 0
#> 13 14.34 1 54 0 1
#> 81.1 14.06 1 34 0 0
#> 30 17.43 1 78 0 0
#> 92.1 22.92 1 47 0 1
#> 157.1 15.10 1 47 0 0
#> 114.1 13.68 1 NA 0 0
#> 167.1 15.55 1 56 1 0
#> 153.1 21.33 1 55 1 0
#> 105.1 19.75 1 60 0 0
#> 107 11.18 1 54 1 0
#> 50 10.02 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 134 17.81 1 47 1 0
#> 63 22.77 1 31 1 0
#> 194.1 22.40 1 38 0 1
#> 125 15.65 1 67 1 0
#> 123 13.00 1 44 1 0
#> 134.1 17.81 1 47 1 0
#> 26 15.77 1 49 0 1
#> 197 21.60 1 69 1 0
#> 29.3 15.45 1 68 1 0
#> 199.1 19.81 1 NA 0 1
#> 107.1 11.18 1 54 1 0
#> 169 22.41 1 46 0 0
#> 45 17.42 1 54 0 1
#> 101 9.97 1 10 0 1
#> 42 12.43 1 49 0 1
#> 158 20.14 1 74 1 0
#> 180 14.82 1 37 0 0
#> 52 10.42 1 52 0 1
#> 105.2 19.75 1 60 0 0
#> 97.1 19.14 1 65 0 1
#> 195 11.76 1 NA 1 0
#> 6.2 15.64 1 39 0 0
#> 66 22.13 1 53 0 0
#> 89.1 11.44 1 NA 0 0
#> 159 10.55 1 50 0 1
#> 96.1 14.54 1 33 0 1
#> 155 13.08 1 26 0 0
#> 184.1 17.77 1 38 0 0
#> 63.1 22.77 1 31 1 0
#> 86 23.81 1 58 0 1
#> 188.1 16.16 1 46 0 1
#> 190 20.81 1 42 1 0
#> 166.1 19.98 1 48 0 0
#> 97.2 19.14 1 65 0 1
#> 88 18.37 1 47 0 0
#> 99 21.19 1 38 0 1
#> 40 18.00 1 28 1 0
#> 59 10.16 1 NA 1 0
#> 92.2 22.92 1 47 0 1
#> 8.1 18.43 1 32 0 0
#> 81.2 14.06 1 34 0 0
#> 18 15.21 1 49 1 0
#> 180.1 14.82 1 37 0 0
#> 170.2 19.54 1 43 0 1
#> 101.1 9.97 1 10 0 1
#> 92.3 22.92 1 47 0 1
#> 169.1 22.41 1 46 0 0
#> 187 9.92 1 39 1 0
#> 69 23.23 1 25 0 1
#> 90 20.94 1 50 0 1
#> 130.2 16.47 1 53 0 1
#> 25 6.32 1 34 1 0
#> 56 12.21 1 60 0 0
#> 49 12.19 1 48 1 0
#> 133 14.65 1 57 0 0
#> 98 24.00 0 34 1 0
#> 191 24.00 0 60 0 1
#> 84 24.00 0 39 0 1
#> 178 24.00 0 52 1 0
#> 98.1 24.00 0 34 1 0
#> 74 24.00 0 43 0 1
#> 161 24.00 0 45 0 0
#> 67 24.00 0 25 0 0
#> 200 24.00 0 64 0 0
#> 163 24.00 0 66 0 0
#> 33 24.00 0 53 0 0
#> 172 24.00 0 41 0 0
#> 147 24.00 0 76 1 0
#> 75 24.00 0 21 1 0
#> 94 24.00 0 51 0 1
#> 54 24.00 0 53 1 0
#> 87 24.00 0 27 0 0
#> 7 24.00 0 37 1 0
#> 34 24.00 0 36 0 0
#> 65 24.00 0 57 1 0
#> 34.1 24.00 0 36 0 0
#> 3 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 7.1 24.00 0 37 1 0
#> 193 24.00 0 45 0 1
#> 87.1 24.00 0 27 0 0
#> 94.1 24.00 0 51 0 1
#> 163.1 24.00 0 66 0 0
#> 65.1 24.00 0 57 1 0
#> 9 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 71.1 24.00 0 51 0 0
#> 173 24.00 0 19 0 1
#> 98.2 24.00 0 34 1 0
#> 148 24.00 0 61 1 0
#> 98.3 24.00 0 34 1 0
#> 12 24.00 0 63 0 0
#> 151 24.00 0 42 0 0
#> 44 24.00 0 56 0 0
#> 174 24.00 0 49 1 0
#> 71.2 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 82 24.00 0 34 0 0
#> 46 24.00 0 71 0 0
#> 38 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 44.1 24.00 0 56 0 0
#> 54.1 24.00 0 53 1 0
#> 34.2 24.00 0 36 0 0
#> 19 24.00 0 57 0 1
#> 131 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 94.2 24.00 0 51 0 1
#> 9.1 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 200.1 24.00 0 64 0 0
#> 67.1 24.00 0 25 0 0
#> 19.1 24.00 0 57 0 1
#> 131.1 24.00 0 66 0 0
#> 122.1 24.00 0 66 0 0
#> 193.1 24.00 0 45 0 1
#> 62 24.00 0 71 0 0
#> 141 24.00 0 44 1 0
#> 74.1 24.00 0 43 0 1
#> 172.1 24.00 0 41 0 0
#> 17.1 24.00 0 38 0 1
#> 121 24.00 0 57 1 0
#> 146 24.00 0 63 1 0
#> 48.1 24.00 0 31 1 0
#> 62.1 24.00 0 71 0 0
#> 112.1 24.00 0 61 0 0
#> 198 24.00 0 66 0 1
#> 103 24.00 0 56 1 0
#> 3.1 24.00 0 31 1 0
#> 112.2 24.00 0 61 0 0
#> 119 24.00 0 17 0 0
#> 62.2 24.00 0 71 0 0
#> 74.2 24.00 0 43 0 1
#> 20 24.00 0 46 1 0
#> 178.1 24.00 0 52 1 0
#> 47 24.00 0 38 0 1
#> 165 24.00 0 47 0 0
#> 3.2 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 137.1 24.00 0 45 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.567 NA NA NA
#> 2 age, Cure model 0.00858 NA NA NA
#> 3 grade_ii, Cure model 0.00611 NA NA NA
#> 4 grade_iii, Cure model 1.07 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00879 NA NA NA
#> 2 grade_ii, Survival model 0.256 NA NA NA
#> 3 grade_iii, Survival model -0.287 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.567025 0.008579 0.006108 1.071734
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 252.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.567025003 0.008579176 0.006108458 1.071733929
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008794123 0.256437568 -0.287145636
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 4.270961e-01 2.137884e-01 3.075813e-01 1.795083e-01 1.335154e-01
#> [6] 4.977218e-01 4.270961e-01 6.952259e-02 7.970699e-01 2.500213e-01
#> [11] 5.582569e-01 2.684364e-01 5.880913e-02 6.215839e-01 3.177595e-01
#> [16] 4.977218e-01 1.951293e-03 9.552447e-01 4.977218e-01 3.705746e-01
#> [21] 9.700710e-01 7.112854e-04 1.335154e-01 3.597141e-01 2.975613e-01
#> [26] 2.049294e-01 7.144480e-01 7.692934e-01 7.831221e-01 6.693185e-03
#> [31] 4.737714e-01 4.617702e-01 4.814170e-02 3.816036e-01 1.555326e-01
#> [36] 3.177595e-01 7.555217e-01 3.388030e-02 6.476245e-01 6.743433e-01
#> [41] 3.488588e-01 1.131349e-01 6.609119e-01 6.743433e-01 2.779752e-01
#> [46] 6.693185e-03 5.582569e-01 4.737714e-01 5.880913e-02 1.131349e-01
#> [51] 8.536850e-01 1.001027e-01 2.319841e-01 1.836350e-02 3.388030e-02
#> [56] 4.154922e-01 7.417923e-01 2.319841e-01 4.039793e-01 5.339654e-02
#> [61] 4.977218e-01 8.536850e-01 2.572771e-02 2.876793e-01 9.112298e-01
#> [66] 8.110708e-01 9.365955e-02 5.833093e-01 8.966316e-01 1.131349e-01
#> [71] 1.555326e-01 4.270961e-01 4.306181e-02 8.821571e-01 6.215839e-01
#> [76] 7.280939e-01 2.500213e-01 1.836350e-02 7.730395e-05 3.816036e-01
#> [81] 8.735776e-02 1.001027e-01 1.555326e-01 1.962459e-01 6.952259e-02
#> [86] 2.228881e-01 6.693185e-03 1.795083e-01 6.743433e-01 5.457788e-01
#> [91] 5.833093e-01 1.335154e-01 9.112298e-01 6.693185e-03 2.572771e-02
#> [96] 9.404833e-01 4.036933e-03 8.110431e-02 3.177595e-01 9.850308e-01
#> [101] 8.251967e-01 8.394224e-01 6.086643e-01 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00
#>
#> $Time
#> 6 51 171 8 170 29 6.1 36 37 184 157 111 153
#> 15.64 18.23 16.57 18.43 19.54 15.45 15.64 21.19 12.52 17.77 15.10 17.45 21.33
#> 96 130 29.1 164 183 29.2 5 77 168 170.1 192 23 108
#> 14.54 16.47 15.45 23.60 9.24 15.45 16.43 7.27 23.72 19.54 16.44 16.92 18.29
#> 60 140 177 92 167 39 175 188 97 130.1 14 194 57
#> 13.15 12.68 12.53 22.92 15.55 15.59 21.91 16.16 19.14 16.47 12.89 22.40 14.46
#> 81 181 105 13 81.1 30 92.1 157.1 167.1 153.1 105.1 107 166
#> 14.06 16.46 19.75 14.34 14.06 17.43 22.92 15.10 15.55 21.33 19.75 11.18 19.98
#> 134 63 194.1 125 123 134.1 26 197 29.3 107.1 169 45 101
#> 17.81 22.77 22.40 15.65 13.00 17.81 15.77 21.60 15.45 11.18 22.41 17.42 9.97
#> 42 158 180 52 105.2 97.1 6.2 66 159 96.1 155 184.1 63.1
#> 12.43 20.14 14.82 10.42 19.75 19.14 15.64 22.13 10.55 14.54 13.08 17.77 22.77
#> 86 188.1 190 166.1 97.2 88 99 40 92.2 8.1 81.2 18 180.1
#> 23.81 16.16 20.81 19.98 19.14 18.37 21.19 18.00 22.92 18.43 14.06 15.21 14.82
#> 170.2 101.1 92.3 169.1 187 69 90 130.2 25 56 49 133 98
#> 19.54 9.97 22.92 22.41 9.92 23.23 20.94 16.47 6.32 12.21 12.19 14.65 24.00
#> 191 84 178 98.1 74 161 67 200 163 33 172 147 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 54 87 7 34 65 34.1 3 71 7.1 193 87.1 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163.1 65.1 9 112 71.1 173 98.2 148 98.3 12 151 44 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.2 185 35 160 122 82 46 38 17 44.1 54.1 34.2 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 48 94.2 9.1 137 200.1 67.1 19.1 131.1 122.1 193.1 62 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.1 172.1 17.1 121 146 48.1 62.1 112.1 198 103 3.1 112.2 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.2 74.2 20 178.1 47 165 3.2 1 137.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> Formula blueprint:
#>
#> # Predictors: 2
#> # Outcomes: 2
#> Intercept: TRUE
#> Novel Levels: FALSE
#> Composition: tibble
#> Indicators: traditional
#>
#> $cure_blueprint
#> Formula blueprint:
#>
#> # Predictors: 2
#> # Outcomes: 0
#> Intercept: TRUE
#> Novel Levels: FALSE
#> Composition: tibble
#> Indicators: traditional
#>